Role of Spontaneous Brain Activity in Explicit and Implicit Aspects of Cognitive Flexibility under Socially Conflicting Situations: A Resting-state fMRI Study using Fractional Amplitude of Low-frequency Fluctuations

We are constantly exposed to socially conflicting situations in everyday life, and cognitive flexibility is essential for adaptively coping with such difficulties. Flexible goal choice and pursuit are not exclusively conscious, and therefore cognitive flexibility involves both explicit and implicit forms of processing. However, it is unclear how individual differences in explicit and implicit aspects of flexibility are associated with neural activity in a resting state. Here, we measured intrinsic fractional amplitude of low-frequency fluctuations (fALFF) by resting-state functional magnetic resonance imaging (RS-fMRI) as an indicator of regional brain spontaneous activity, together with explicit and implicit aspects of cognitive flexibility using the Cognitive Flexibility Scale (CFS) and Implicit Association Test (IAT). Consistent with the dual processing theory, there was a strong association between explicit aspects of flexibility (CFS score) and "rationalism" thinking style and between implicit aspects (IAT effect) and "experientialism." The level of explicit flexibility was also correlated with fALFF values in the left lateral prefrontal cortex, whereas the level of implicit flexibility was correlated with fALFF values in the right cerebellum. Furthermore, the fALFF values in both regions predicted individual preference for flexible decision-making strategy in a vignettes simulation task. These results add to our understanding of the neural mechanisms underlying flexible decision-making for solving social conflicts. More generally, our findings highlight the utility of RS-fMRI combined with both explicit and implicit psychometric measures for better understanding individual differences in social cognition.

[1]  Olaf Sporns,et al.  Connectivity and complexity: the relationship between neuroanatomy and brain dynamics , 2000, Neural Networks.

[2]  Carol A. Seger,et al.  Implicit learning. , 1994, Psychological bulletin.

[3]  M. Haruno,et al.  Activity in the amygdala elicited by unfair divisions predicts social value orientation , 2009, Nature Neuroscience.

[4]  Jonathan Evans Dual-processing accounts of reasoning, judgment, and social cognition. , 2008, Annual review of psychology.

[5]  J. Talairach,et al.  Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging , 1988 .

[6]  Peter Reilly,et al.  Balancing Flexibility—Meeting the Interests of Employer and Employee , 1998 .

[7]  Dean Mobbs,et al.  Law, Responsibility, and the Brain , 2007, PLoS biology.

[8]  J. Tanji,et al.  Concept-based behavioral planning and the lateral prefrontal cortex , 2007, Trends in Cognitive Sciences.

[9]  Fumitoshi Kodaka,et al.  Honesty mediates the relationship between serotonin and reaction to unfairness , 2012, Proceedings of the National Academy of Sciences.

[10]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[11]  R. Kawashima,et al.  Adaptive ability to cope with atypical or novel situations involving tool use: An fMRI approach , 2015, Neuroscience Research.

[12]  Matthew D. Lieberman,et al.  Social cognitive neuroscience: a review of core processes. , 2007, Annual review of psychology.

[13]  S. Shimojo,et al.  Functional connectivity of the striatum in experts of stenography , 2015, Brain and behavior.

[14]  Masao Ito Control of mental activities by internal models in the cerebellum , 2008, Nature Reviews Neuroscience.

[15]  E. Shimizu,et al.  Development and validation of the Japanese version of cognitive flexibility scale , 2016, BMC Research Notes.

[16]  Colin Camerer,et al.  Neural mechanisms and personality correlates of the sunk cost effect , 2016, Scientific Reports.

[17]  Sébastien Ourselin,et al.  Automatic Brain , 2019 .

[18]  Henrik Walter,et al.  Striatal activation as a neural link between cognitive and perceptual flexibility , 2016, NeuroImage.

[19]  D. Matsuzawa,et al.  Feasibility of cognitive remediation therapy for adults with autism spectrum disorders: a single-group pilot study , 2017, Neuropsychiatric disease and treatment.

[20]  Dana Chidekel,et al.  Adaptation, Expertise, and Giftedness: Towards an Understanding of Cortical, Subcortical, and Cerebellar Network Contributions , 2010, The Cerebellum.

[21]  Wei Chen,et al.  Amplitude of Low-Frequency Oscillations in First-Episode, Treatment-Naive Patients with Major Depressive Disorder: A Resting-State Functional MRI Study , 2012, PloS one.

[22]  Mike Oaksford,et al.  Imaging deductive reasoning and the new paradigm , 2015, Front. Hum. Neurosci..

[23]  Frank Van Overwalle,et al.  Social cognition and the cerebellum: A meta-analysis of over 350 fMRI studies , 2014, NeuroImage.

[24]  E. Cabanis,et al.  The Human Brain: Surface, Three-Dimensional Sectional Anatomy and Mri , 1991 .

[25]  Gereon R Fink,et al.  The right temporoparietal junction in attention and social interaction: A transcranial magnetic stimulation study , 2016, Human brain mapping.

[26]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited—Again , 1995, NeuroImage.

[27]  Luke McNally,et al.  Cooperation and the evolution of intelligence , 2012, Proceedings of the Royal Society B: Biological Sciences.

[28]  M. Brammer,et al.  Neural correlates of switching set as measured in fast, event‐related functional magnetic resonance imaging , 2004, Human brain mapping.

[29]  T. Suslow,et al.  Automatic brain response to facial emotion as a function of implicitly and explicitly measured extraversion , 2010, Neuroscience.

[30]  Angie A. Kehagia,et al.  Learning and cognitive flexibility: frontostriatal function and monoaminergic modulation , 2010, Current Opinion in Neurobiology.

[31]  Jukka-Pekka Kauppi,et al.  Collaborative roles of Temporoparietal Junction and Dorsolateral Prefrontal Cortex in Different Types of Behavioural Flexibility , 2017, Scientific Reports.

[32]  R. Rubin,et al.  A New Measure of Cognitive Flexibility , 1995 .

[33]  H. Imamizu,et al.  Neural Substrates Related to Motor Memory with Multiple Timescales in Sensorimotor Adaptation , 2015, PLoS biology.

[34]  Susan M. Ravizza,et al.  Shifting set about task switching: Behavioral and neural evidence for distinct forms of cognitive flexibility , 2008, Neuropsychologia.

[35]  Gloria E. Wheeler,et al.  An empirical study of ethical predispositions , 1996 .

[36]  E. Paulesu,et al.  Guess who’s coming to dinner: Brain signatures of racially biased and politically correct behaviors , 2016, Neuroscience.

[37]  E. Koechlin,et al.  The Architecture of Cognitive Control in the Human Prefrontal Cortex , 2003, Science.

[38]  章 坂元,et al.  情報処理スタイル(合理性-直観性)尺度の作成 , 2004 .

[39]  H. Geurts,et al.  The paradox of cognitive flexibility in autism , 2009, Trends in Cognitive Sciences.

[40]  M. Raichle Two views of brain function , 2010, Trends in Cognitive Sciences.

[41]  A. Belger,et al.  Neural correlates of impaired cognitive-behavioral flexibility in anorexia nervosa. , 2009, The American journal of psychiatry.

[42]  Yasuyuki Gondo,et al.  日本版NEO-PI-Rの作成とその因子的妥当性の検討 , 1998 .

[43]  E. Fehr A Theory of Fairness, Competition and Cooperation , 1998 .

[44]  J. Devin McAuley,et al.  Individual differences in resting-state functional connectivity with the executive network: support for a cerebellar role in anxiety vulnerability , 2015, Brain Structure and Function.

[45]  Tsukasa Kato Development of the Coping Flexibility Scale: evidence for the coping flexibility hypothesis. , 2012, Journal of counseling psychology.

[46]  K. Hutchison,et al.  Substance use disorders: a theory‐driven approach to the integration of genetics and neuroimaging , 2013, Annals of the New York Academy of Sciences.

[47]  B. Gold,et al.  Common and Distinct Mechanisms of Cognitive Flexibility in Prefrontal Cortex , 2011, The Journal of Neuroscience.

[48]  Matthew M. Martin,et al.  An Examination of Aggression and Adaption Traits with Moral Foundation , 2015 .

[49]  A. Luft,et al.  Predictive value and reward in implicit classification learning , 2013, Human brain mapping.

[50]  T. Suslow,et al.  Brain response to masked and unmasked facial emotions as a function of implicit and explicit personality self-concept of extraversion , 2017, Neuroscience.

[51]  S Epstein,et al.  The relation of rational and experiential information processing styles to personality, basic beliefs, and the ratio-bias phenomenon. , 1999, Journal of personality and social psychology.

[52]  Thomas T. Liu,et al.  Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI , 2012, NeuroImage.

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

[54]  M. Crockett The Neurochemistry of Fairness , 2009, Annals of the New York Academy of Sciences.

[55]  Hesheng Liu,et al.  State-dependent variability of dynamic functional connectivity between frontoparietal and default networks relates to cognitive flexibility , 2016, Neuroscience.

[56]  A. Greenwald,et al.  Measuring individual differences in implicit cognition: the implicit association test. , 1998, Journal of personality and social psychology.

[57]  Brian A. Nosek,et al.  Understanding and Using the Implicit Association Test: IV: What We Know (So Far) about the Method. , 2007 .

[58]  J. Desmond,et al.  Neuroimaging studies of the cerebellum: language, learning and memory , 1998, Trends in Cognitive Sciences.

[59]  W. Bank The Human Brain. Surface, Three-Dimensional Sectional Anatomy and MRI , 1993 .

[60]  H. Duvernoy,et al.  The Human Brain: Surface, Three-Dimensional Sectional Anatomy with MRI, and Blood Supply , 1999 .

[61]  S. Huettel,et al.  The functional neuroanatomy of decision making: Prefrontal control of thought and action , 2012, Brain Research.

[62]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[63]  Rajka Smiljanic,et al.  The neural processing of foreign-accented speech and its relationship to listener bias , 2014, Front. Hum. Neurosci..

[64]  R. Hashimoto,et al.  Attitudes toward risk and ambiguity in patients with autism spectrum disorder , 2017, Molecular Autism.

[65]  Rand J. Spiro,et al.  Cognitive flexibility theory : advanced knowledge acquisition in ill-structured domains , 1988 .

[66]  Chaozhe Zhu,et al.  An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF , 2008, Journal of Neuroscience Methods.

[67]  Gerd Gigerenzer,et al.  Heuristic decision making. , 2011, Annual review of psychology.

[68]  Yasumasa Okamoto,et al.  Personality traits and the amplitude of spontaneous low-frequency oscillations during resting state , 2011, Neuroscience Letters.

[69]  Christine L. Cox,et al.  The balance between feeling and knowing: affective and cognitive empathy are reflected in the brain's intrinsic functional dynamics. , 2012, Social cognitive and affective neuroscience.

[70]  Matthew D. Lieberman,et al.  Serotonin Modulates Behavioral Reactions to Unfairness , 2008, Science.

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

[72]  R. Cameron Craddock,et al.  A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics , 2013, NeuroImage.

[73]  F. Crescenzo,et al.  Implicit learning in individuals with autism spectrum disorders: a meta-analysis , 2014, Psychological Medicine.

[74]  Manuel Graña,et al.  Discrimination of Schizophrenia Auditory Hallucinators by Machine Learning of Resting-State Functional MRI , 2015, Int. J. Neural Syst..

[75]  Huafu Chen,et al.  Specific frequency bands of amplitude low‐frequency oscillation encodes personality , 2014, Human brain mapping.

[76]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[77]  F. Foti,et al.  Cerebellar involvement in cognitive flexibility , 2009, Neurobiology of Learning and Memory.

[78]  U. Frith,et al.  Mindblind Eyes: An Absence of Spontaneous Theory of Mind in Asperger Syndrome , 2009, Science.

[79]  J. V. Vander Wal,et al.  The Cognitive Flexibility Inventory: Instrument Development and Estimates of Reliability and Validity , 2010, Cognitive Therapy and Research.

[80]  Brian A. Nosek,et al.  Understanding and using the implicit association test: I. An improved scoring algorithm. , 2003, Journal of personality and social psychology.

[81]  D. Lagnado,et al.  Probabilistic classification learning with corrective feedback is associated with in vivo striatal dopamine release in the ventral striatum, while learning without feedback is not , 2014, Human brain mapping.

[82]  U. Frith Mind Blindness and the Brain in Autism , 2001, Neuron.

[83]  S. Kosslyn,et al.  Cognitive Style as Environmentally Sensitive Individual Differences in Cognition , 2014, Psychological science in the public interest : a journal of the American Psychological Society.

[84]  Bernhard Hommel,et al.  Intelligence and cognitive flexibility: Fluid intelligence correlates with feature “unbinding” across perception and action , 2006, Psychonomic bulletin & review.

[85]  Jonathan D. Power,et al.  Multi-task connectivity reveals flexible hubs for adaptive task control , 2013, Nature Neuroscience.

[86]  H. Aarts,et al.  The Unconscious Will: How the Pursuit of Goals Operates Outside of Conscious Awareness , 2010, Science.

[87]  Steven K. Jahns,et al.  Ergonomics Society of the Human Factors and Human Factors: The Journal , 2013 .

[88]  Magdalena Ietswaart,et al.  Social behavior following traumatic brain injury and its association with emotion recognition, understanding of intentions, and cognitive flexibility , 2008, Journal of the International Neuropsychological Society.

[89]  Kristin K. Andersen,et al.  Intergenerational patterns of cognitive flexibility through expressions of maternal care , 2017 .

[90]  Xueting Li,et al.  The shared neural basis of music and language , 2017, Neuroscience.

[91]  T. Milner,et al.  Functionally Specific Changes in Resting-State Sensorimotor Networks after Motor Learning , 2011, The Journal of Neuroscience.

[92]  L. Jäncke,et al.  Takotsubo Syndrome – Predictable from brain imaging data , 2017, Scientific Reports.

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

[94]  S. Orsillo,et al.  Investigating cognitive flexibility as a potential mechanism of mindfulness in Generalized Anxiety Disorder. , 2014, Journal of behavior therapy and experimental psychiatry.

[95]  X. Wang,et al.  Regional amplitude of the low-frequency fluctuations at rest predicts word-reading skill , 2015, Neuroscience.

[96]  Yu-Te Wu,et al.  The patterns of fractional amplitude of low-frequency fluctuations in depression patients: the dissociation between temporal regions and fronto-parietal regions. , 2015, Journal of affective disorders.

[97]  J. Kwon,et al.  Neural correlates of cognitive inflexibility during task-switching in obsessive-compulsive disorder. , 2007, Brain : a journal of neurology.

[98]  M. Corbetta,et al.  Learning sculpts the spontaneous activity of the resting human brain , 2009, Proceedings of the National Academy of Sciences.

[99]  Colin Camerer,et al.  Self-control in decision-making involves modulation of the vmPFC valuation system , 2009, NeuroImage.

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

[101]  Yasuyuki Taki,et al.  Degree centrality and fractional amplitude of low-frequency oscillations associated with Stroop interference , 2015, NeuroImage.

[102]  S. Lui,et al.  Spontaneous neural activity alterations in temporomandibular disorders: A cross-sectional and longitudinal resting-state functional magnetic resonance imaging study , 2014, Neuroscience.