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      Testosterone Modulates Altered Prefrontal Control of Emotional Actions in Psychopathic Offenders123

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          Abstract

          Psychopathic individuals are notorious for their controlled goal-directed aggressive behavior. Yet, during social challenges, they often show uncontrolled emotional behavior. Healthy individuals can control their social emotional behavior through anterior prefrontal cortex (aPFC) downregulation of neural activity in the amygdala, with testosterone modulating aPFC–amygdala coupling. This study tests whether individual differences in this neuroendocrine system relate to the paradoxical lack of emotional control observed in human psychopathic offenders. Emotional control was operationalized with an fMRI-adapted approach–avoidance task requiring rule-driven control over rapid emotional responses. Fifteen psychopathic offenders and 19 matched healthy control subjects made approaching and avoiding movements in response to emotional faces. Control of social emotional behavior was required during affect-incongruent trials, when participants had to override affect-congruent, automatic action tendencies and select the opposite response. Psychopathic offenders showed less control-related aPFC activity and aPFC–amygdala coupling during trials requiring control of emotional actions, when compared with healthy control subjects. This pattern was particularly pronounced in psychopathic individuals with high endogenous testosterone levels. These findings suggest that reduced prefrontal coordination underlies reduced behavioral control in psychopathic offenders during emotionally provoking situations. Even though the modest sample size warrants replication, the modulatory role of endogenous testosterone on the aPFC–amygdala circuit suggests a neurobiological substrate of individual differences that is relevant for the advancement of treatment and the reduction of recidivism.

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          The assessment and analysis of handedness: The Edinburgh inventory

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            Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.

            An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute (MNI) (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468) was performed. The MNI single-subject main sulci were first delineated and further used as landmarks for the 3D definition of 45 anatomical volumes of interest (AVOI) in each hemisphere. This procedure was performed using a dedicated software which allowed a 3D following of the sulci course on the edited brain. Regions of interest were then drawn manually with the same software every 2 mm on the axial slices of the high-resolution MNI single subject. The 90 AVOI were reconstructed and assigned a label. Using this parcellation method, three procedures to perform the automated anatomical labeling of functional studies are proposed: (1) labeling of an extremum defined by a set of coordinates, (2) percentage of voxels belonging to each of the AVOI intersected by a sphere centered by a set of coordinates, and (3) percentage of voxels belonging to each of the AVOI intersected by an activated cluster. An interface with the Statistical Parametric Mapping package (SPM, J. Ashburner and K. J. Friston, 1999, Hum. Brain Mapp. 7, 254-266) is provided as a freeware to researchers of the neuroimaging community. We believe that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain in which deformations are well known. However, this tool does not alleviate the need for more sophisticated labeling strategies based on anatomical or cytoarchitectonic probabilistic maps.
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              Unified segmentation.

              A probabilistic framework is presented that enables image registration, tissue classification, and bias correction to be combined within the same generative model. A derivation of a log-likelihood objective function for the unified model is provided. The model is based on a mixture of Gaussians and is extended to incorporate a smooth intensity variation and nonlinear registration with tissue probability maps. A strategy for optimising the model parameters is described, along with the requisite partial derivatives of the objective function.
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                Author and article information

                Journal
                eNeuro
                eNeuro
                eneuro
                eneuro
                eNeuro
                eNeuro
                Society for Neuroscience
                2373-2822
                15 January 2016
                8 February 2016
                Jan-Feb 2016
                : 3
                : 1
                : ENEURO.0107-15.2016
                Affiliations
                [1 ]Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London , London WC1N 3BG, United Kingdom
                [2 ]Behavioural Science Institute, Radboud University Nijmegen , 6525 HR, Nijmegen, The Netherlands
                [3 ]Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen , 6525 EN, Nijmegen, The Netherlands
                [4 ]Department of Psychiatry, UMC Sint Radboud , 6525 GA, Nijmegen, The Netherlands
                [5 ]Pompestichting , 6532 CN, Nijmegen, The Netherlands
                Author notes
                [1]

                The authors declare no competing financial interests.

                [2]

                Author contributions: I.V., A.K.L.v.B., B.H.B., R.J.V., I.T., and K.R. designed research; I.V. and A.K.L.v.B. performed research; I.V., A.K.L.v.B., I.T., and K.R. analyzed data; and I.V., A.K.L.v.B., B.H.B., R.J.V., I.T., and K.R. wrote the paper.

                [3]

                This work was supported by VIDI Grant 452-07-008 from the Netherlands Organization for Scientific Research (NWO) awarded to K.R. supporting I.V., Marie Curie Individual Fellowship MSCA-IF-2014-EF_660397 within the European Union's Horizon 2020 Framework Programme awarded to I.V., VICI Grant 453-08-002 from the NWO awarded to I.T., and Starting Grant ERC_StG2012_313749 from the European Research Council and VICI Grant 453-12-001 from the NWO awarded to K.R.

                Correspondence should be addressed to Inge Volman, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, Box 146, 33 Queen Square, London WC1N 3BG, UK; Email: i.volman@ 123456ucl.ac.uk .
                Author information
                http://orcid.org/0000-0003-3467-1841
                http://orcid.org/0000-0003-0936-3601
                http://orcid.org/0000-0002-8863-8978
                Article
                eN-NWR-0107-15
                10.1523/ENEURO.0107-15.2016
                4745181
                26878057
                d3bd44b6-f7ce-44c8-b569-d548718d76f8
                Copyright © 2016 Volman et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                History
                : 15 September 2015
                : 15 December 2015
                : 3 January 2016
                Page count
                Figures: 4, Tables: 3, Equations: 0, References: 76, Pages: 12, Words: 9754
                Funding
                Funded by: Netherlands organisation for scientific research
                Award ID: 452-07-008
                Funded by: Netherlands organisation for scientific research
                Award ID: 453-08-002
                Funded by: European research council
                Award ID: ERC_StG2012_313749
                Categories
                1
                New Research
                Cognition and Behavior
                Custom metadata
                January/February 2016

                amygdala,connectivity,emotion,fmri,prefrontal,psychopathy
                amygdala, connectivity, emotion, fmri, prefrontal, psychopathy

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