Functional connectivity in the resting brain as biological correlate of the Affective Neuroscience Personality Scales

ABSTRACT According to Jaak Panksepp's Affective Neuroscience Theory and the derived self‐report measure, the Affective Neuroscience Personality Scales (ANPS), differences in the responsiveness of primary emotional systems form the basis of human personality. In order to investigate neuronal correlates of personality, the underlying neuronal circuits of the primary emotional systems were analyzed in the present fMRI‐study by associating the ANPS to functional connectivity in the resting brain. N=120 healthy participants were invited for the present study. The results were reinvestigated in an independent, smaller sample of N=52 participants. A seed‐based whole brain approach was conducted with seed‐regions bilaterally in the basolateral and superficial amygdalae. The selection of seed‐regions was based on meta‐analytic data on affective processing and the Juelich histological atlas. Multiple regression analyses on the functional connectivity maps revealed associations with the SADNESS‐scale in both samples. Functional resting‐state connectivity between the left basolateral amygdala and a cluster in the postcentral gyrus, and between the right basolateral amygdala and clusters in the superior parietal lobe and subgyral in the parietal lobe was associated with SADNESS. No other ANPS‐scale revealed replicable results. The present findings give first insights into the neuronal basis of the SADNESS‐scale of the ANPS and support the idea of underlying neuronal circuits. In combination with previous research on genetic associations of the ANPS functional resting‐state connectivity is discussed as a possible endophenotype of personality. HIGHLIGHTSThe Affective Neuroscience Personality Scales are a new psychometric tool.We investigate their neurobiological correlates using resting‐state fMRI.Seed‐Regions were selected based on meta‐analysis and cytoarchitecture.Connectivity of the basolateral amygdala is linked to SADNESS.Consistent results are obtained in two independent samples.

[1]  Christian J. Fiebach,et al.  The biological basis of anger: Associations with the gene coding for DARPP-32 (PPP1R1B) and with amygdala volume , 2009, Behavioural Brain Research.

[2]  Helmut von Bracken,et al.  Gestalt und Wachstum in der Persönlichkeit , 1970 .

[3]  Yasumasa Okamoto,et al.  Sadness enhances the experience of pain via neural activation in the anterior cingulate cortex and amygdala: An fMRI study , 2010, NeuroImage.

[4]  J. Panksepp,et al.  The brain's emotional foundations of human personality and the Affective Neuroscience Personality Scales , 2011, Neuroscience & Biobehavioral Reviews.

[5]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[6]  Mitsutoshi Okazaki,et al.  Revised NEO Personality Inventory（NEO-PI-R）を用いたてんかん患者におけるパーソナリティ傾向に関する検討 , 2018 .

[7]  Christian Montag,et al.  Genetically determined dopamine availability predicts disposition for depression , 2011, Brain and behavior.

[8]  Norihiro Sadato,et al.  Volume of left amygdala subregion predicted temperamental trait of harm avoidance in female young subjects. A voxel-based morphometry study , 2006, Brain Research.

[9]  Nanyin Zhang,et al.  Amygdala–orbitofrontal resting‐state functional connectivity is associated with trait anger , 2012, Neuroreport.

[10]  Alberto Llera,et al.  ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data , 2015, NeuroImage.

[11]  Robert L. Lloyd,et al.  AMYGDALOID ELECTRICAL ACTIVITY IN RESPONSE TO CONSPECIFIC CALLS IN SQUIRREL MONKEY (S. SCIUREUS): INFLUENCE OF ENVIRONMENTAL SETTING, CORTICAL INPUTS, AND RECORDING SITE , 1988 .

[12]  J. Panksepp,et al.  The Affective Neuroscience Personality Scales: Normative Data and Implications , 2003 .

[13]  Simon B. Eickhoff,et al.  A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data , 2005, NeuroImage.

[14]  Xi-Nian Zuo,et al.  Genetic and Environmental Contributions to Functional Connectivity Architecture of the Human Brain , 2016, Cerebral cortex.

[15]  Yong He,et al.  BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics , 2013, PloS one.

[16]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[17]  P. F. Buckley.  Interaction of 5-HTTLPR and a Variation on the Oxytocin Receptor Gene Influences Negative Emotionality , 2012 .

[18]  J. Newman.  The Physiological Control of Mammalian Vocalization , 1988, Springer US.

[19]  Simon B. Eickhoff,et al.  Assignment of functional activations to probabilistic cytoarchitectonic areas revisited , 2007, NeuroImage.

[20]  Stephen M. Smith,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[21]  Karl J. Friston,et al.  Functional Connectivity: The Principal-Component Analysis of Large (PET) Data Sets , 1993, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[22]  Yufeng Zang,et al.  DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI , 2010 .

[23]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[24]  L. Williams,et al.  Establishing the resting state default mode network derived from functional magnetic resonance imaging tasks as an endophenotype: A twins study , 2014, Human brain mapping.

[25]  I. Gottesman,et al.  The endophenotype concept in psychiatry: etymology and strategic intentions. , 2003, The American journal of psychiatry.

[26]  Daniel S. Margulies,et al.  Functional connectivity of the human amygdala using resting state fMRI , 2009, NeuroImage.

[27]  J. Panksepp.  Cross-Species Affective Neuroscience Decoding of the Primal Affective Experiences of Humans and Related Animals , 2011, PloS one.

[28]  Jonathan S. Adelstein,et al.  Personality Is Reflected in the Brain's Intrinsic Functional Architecture , 2011, PloS one.

[29]  Alfonso Barrós-Loscertales,et al.  Behavioral Inhibition System activity is associated with increased amygdala and hippocampal gray matter volume: A voxel-based morphometry study , 2006, NeuroImage.

[30]  Chris Rorden,et al.  Improving Lesion-Symptom Mapping , 2007, Journal of Cognitive Neuroscience.

[31]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[32]  S. Paradiso,et al.  Book Review: Affective Neuroscience: The Foundations of Human and Animal Emotions , 2000 .

[33]  Yasumasa Okamoto,et al.  Sadness enhances the experience of pain and affects pain-evoked cortical activities: an MEG study. , 2012, The journal of pain : official journal of the American Pain Society.

[34]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[35]  Christian Montag,et al.  Anxious personality and functional efficiency of the insular-opercular network: A graph-analytic approach to resting-state fMRI , 2016, Cognitive, affective & behavioral neuroscience.

[36]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[37]  Francesco Fera,et al.  Increased functional connectivity within mesocortical networks in open people , 2015, NeuroImage.

[38]  Paul M. Thompson,et al.  Heritability of the network architecture of intrinsic brain functional connectivity , 2015, NeuroImage.

[39]  Chaogan Yan,et al.  DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI , 2010, Front. Syst. Neurosci..

[40]  Bianca Jupp,et al.  Impaired Limbic Cortico-Striatal Structure and Sustained Visual Attention in a Rodent Model of Schizophrenia , 2014, The international journal of neuropsychopharmacology.

[41]  B. Biswal,et al.  The resting brain: unconstrained yet reliable. , 2009, Cerebral cortex.

[42]  Christian Montag,et al.  Voxelwise eigenvector centrality mapping of the human functional connectome reveals an influence of the catechol-O-methyltransferase val158met polymorphism on the default mode and somatomotor network , 2015, Brain Structure and Function.

[43]  S. Rombouts,et al.  Neuroticism and extraversion are associated with amygdala resting-state functional connectivity , 2014, Cognitive, affective & behavioral neuroscience.

[44]  Peter Kirsch,et al.  Functional characterization of an oxytocin receptor gene variant (rs2268498) previously associated with social cognition by expression analysis in vitro and in human brain biopsy , 2017, Social neuroscience.

[45]  Wei Deng,et al.  Genetic influences on resting‐state functional networks: A twin study , 2015, Human brain mapping.

[46]  Turhan Canli,et al.  Amygdala gray matter concentration is associated with extraversion and neuroticism , 2005, Neuroreport.

[47]  Birgit Völlm,et al.  Oxytocin Affects the Connectivity of the Precuneus and the Amygdala: A Randomized, Double-Blinded, Placebo-Controlled Neuroimaging Trial , 2015, The international journal of neuropsychopharmacology.

[48]  M. Boccia,et al.  Immunohistochemical localization of oxytocin receptors in human brain , 2013, Neuroscience.

[49]  Simon B. Eickhoff,et al.  Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps , 2006, NeuroImage.

[50]  M. Fox,et al.  Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.

[51]  C. Elger,et al.  Intrinsic connectivity networks and personality: The temperament dimension harm avoidance moderates functional connectivity in the resting brain , 2013, Neuroscience.