1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Neuroscience
  4. Volume 44, 2021
  5. Article

Annual Review of Neuroscience

Volume 44, 2021

Adaptive Prediction for Social Contexts: The Cerebellar Contribution to Typical and Atypical Social Behaviors

Abstract

Social interactions involve processes ranging from face recognition to understanding others’ intentions. To guide appropriate behavior in a given context, social interactions rely on accurately predicting the outcomes of one's actions and the thoughts of others. Because social interactions are inherently dynamic, these predictions must be continuously adapted. The neural correlates of social processing have largely focused on emotion, mentalizing, and reward networks, without integration of systems involved in prediction. The cerebellum forms predictive models to calibrate movements and adapt them to changing situations, and cerebellar predictive modeling is thought to extend to nonmotor behaviors. Primary cerebellar dysfunction can produce social deficits, and atypical cerebellar structure and function are reported in autism, which is characterized by social communication challenges and atypical predictive processing. We examine the evidence that cerebellar-mediated predictions and adaptation play important roles in social processes and argue that disruptions in these processes contribute to autism.

Keyword(s): adaptation, autism, cerebellum, implicit, prediction, social
Loading

Article metrics loading...

/content/journals/10.1146/annurev-neuro-100120-092143
2021-07-08
2024-04-20
Loading full text...

Full text loading...

/deliver/fulltext/neuro/44/1/annurev-neuro-100120-092143.html?itemId=/content/journals/10.1146/annurev-neuro-100120-092143&mimeType=html&fmt=ahah

Literature Cited

  1. Allman MJ, Pelphrey KA, Meck WH. 2011. Developmental neuroscience of time and number: implications for autism and other neurodevelopmental disabilities. Front. Integr. Neurosci. 6:7
     [Google Scholar]
  2. Am. Psychiatr. Assoc 2013. Diagnostic and Statistical Manual of Mental Disorders Arlington, VA: Am. Psychiatr. Assoc., 5th ed..
     [Google Scholar]
  3. Apps R, Hawkes R, Aoki S, Bengtsson F, Brown AM et al. 2018. Cerebellar modules and their role as operational cerebellar processing units: a consensus paper. Cerebellum 17:654–82
     [Google Scholar]
  4. Asano E, Chugani D, Muzik O, Behen M, Janisse J et al. 2001. Autism in tuberous sclerosis complex is related to both cortical and subcortical dysfunction. Neurology 57:1269–77
     [Google Scholar]
  5. Badura A, Verpeut JL, Metzger JW, Pereira TD, Pisano TJ et al. 2018. Normal cognitive and social development require posterior cerebellar activity. eLife 7:e36401
     [Google Scholar]
  6. Balsters JH, Apps MAJ, Bolis D, Lehner R, Gallagher L, Wenderoth N. 2016. Disrupted prediction errors index social deficits in autism spectrum disorder. Brain 140:235–46
     [Google Scholar]
  7. Baron-Cohen S, Leslie AM, Frith U. 1985. Does the autistic child have a “theory of mind”?. Cognition 21:37–46
     [Google Scholar]
  8. Baudouin SJ, Gaudias J, Gerharz S, Hatstatt L, Zhou K et al. 2012. Shared synaptic pathophysiology in syndromic and nonsyndromic rodent models of autism. Science 338:128–32
     [Google Scholar]
  9. Bauman ML. 1991. Microscopic neuroanatomic abnormalities in autism. Pediatrics 87:791–96
     [Google Scholar]
  10. Behrens TE, Hunt LT, Woolrich MW, Rushworth MF. 2008. Associative learning of social value. Nature 456:245–49
     [Google Scholar]
  11. Brady RO Jr., Gonsalvez I, Lee I, Ongur D, Seidman LJ et al. 2019. Cerebellar-prefrontal network connectivity and negative symptoms in schizophrenia. Am. J. Psychiatry 176:512–20
     [Google Scholar]
  12. Breska A, Ivry RB. 2016. Taxonomies of timing: Where does the cerebellum fit in?. Curr. Opin. Behav. Sci. 8:282–88
     [Google Scholar]
  13. Brooks JX, Carriot J, Cullen KE. 2015. Learning to expect the unexpected: rapid updating in primate cerebellum during voluntary self-motion. Nat. Neurosci. 18:1310–17
     [Google Scholar]
  14. Brown EC, Brune M. 2012. The role of prediction in social neuroscience. Front. Hum. Neurosci. 6:147
     [Google Scholar]
  15. Buckner RL, Krienen FM, Castellanos A, Diaz JC, Yeo BT. 2011. The organization of the human cerebellum estimated by intrinsic functional connectivity. J. Neurophysiol. 106:2322–45
     [Google Scholar]
  16. Callenmark B, Kjellin L, Rönnqvist L, Bölte S. 2014. Explicit versus implicit social cognition testing in autism spectrum disorder. Autism 18:684–93
     [Google Scholar]
  17. Carta I, Chen CH, Schott AL, Dorizan S, Khodakhah K. 2019. Cerebellar modulation of the reward circuitry and social behavior. Science 363:eaav0581
     [Google Scholar]
  18. Cerminara NL, Lang EJ, Sillitoe RV, Apps R. 2015. Redefining the cerebellar cortex as an assembly of non-uniform Purkinje cell microcircuits. Nat. Rev. Neurosci. 16:79–93
     [Google Scholar]
  19. Chabrol FP, Blot A, Mrsic-Flogel TD. 2019. Cerebellar contribution to preparatory activity in motor neocortex. Neuron 103:506–19.e504
     [Google Scholar]
  20. Chambon V, Farrer C, Pacherie E, Jacquet PO, Leboyer M, Zalla T. 2017. Reduced sensitivity to social priors during action prediction in adults with autism spectrum disorders. Cognition 160:17–26
     [Google Scholar]
  21. Chez MG, Chang M, Krasne V, Coughlan C, Kominsky M, Schwartz A. 2006. Frequency of epileptiform EEG abnormalities in a sequential screening of autistic patients with no known clinical epilepsy from 1996 to 2005. Epilepsy Behav 8:267–71
     [Google Scholar]
  22. Cho KKA, Davidson TJ, Bouvier G, Marshall JD, Schnitzer MJ, Sohal VS. 2020. Cross-hemispheric gamma synchrony between prefrontal parvalbumin interneurons supports behavioral adaptation during rule shift learning. Nat. Neurosci. 23:892–902
     [Google Scholar]
  23. Clausi S, Iacobacci C, Lupo M, Olivito G, Molinari M, Leggio M. 2017. The role of the cerebellum in unconscious and conscious processing of emotions: a review. Appl. Sci. 7:521
     [Google Scholar]
  24. Clausi S, Olivito G, Lupo M, Siciliano L, Bozzali M, Leggio M. 2018. The cerebellar predictions for social interactions: theory of mind abilities in patients with degenerative cerebellar atrophy. Front. Cell Neurosci. 12:510
     [Google Scholar]
  25. Courchesne E, Campbell K, Solso S. 2011. Brain growth across the life span in autism: age-specific changes in anatomical pathology. Brain Res 1380:138–45
     [Google Scholar]
  26. Courchesne E, Yeung-Courchesne R, Hesselink J, Jernigan T. 1988. Hypoplasia of cerebellar vermal lobules VI and VII in autism. New Engl. J. Med. 318:1349–54
     [Google Scholar]
  27. Critchley HD, Daly EM, Bullmore ET, Williams SC, Van Amelsvoort T et al. 2000. The functional neuroanatomy of social behaviour: changes in cerebral blood flow when people with autistic disorder process facial expressions. Brain 123:Pt. 112203–12
     [Google Scholar]
  28. Cupolillo D, Hoxha E, Faralli A, De Luca A, Rossi F et al. 2016. Autistic-like traits and cerebellar dysfunction in Purkinje cell PTEN knock-out mice. Neuropsychopharmacology 41:1457–66
     [Google Scholar]
  29. D'Mello AM, Crocetti D, Mostofsky SH, Stoodley CJ. 2015. Cerebellar gray matter and lobular volumes correlate with core autism symptoms. NeuroImage Clin 7:631–39
     [Google Scholar]
  30. D'Mello AM, Stoodley CJ 2015. Cerebro-cerebellar circuits in autism spectrum disorder. Front. Neurosci. 9:408
     [Google Scholar]
  31. DuBois D, Ameis SH, Lai M-C, Casanova MF, Desarkar P. 2016. Interoception in autism spectrum disorder: a review. Int. J. Dev. Neurosci. 52:104–11
     [Google Scholar]
  32. Duerden EG, Mak-Fan KM, Taylor MJ, Roberts SW. 2012. Regional differences in grey and white matter in children and adults with autism spectrum disorders: an activation likelihood estimate (ALE) meta-analysis. Autism Res 5:49–66
     [Google Scholar]
  33. Eccles JC, Sasaki K, Strata P. 1967. Interpretation of the potential fields generated in the cerebellar cortex by a mossy fibre volley. Exp. Brain Res. 3:58–80
     [Google Scholar]
  34. Eilam D, Izhar R, Mort J 2011. Threat detection: behavioral practices in animals and humans. Neurosci. Biobehav. Rev. 35:999–1006
     [Google Scholar]
  35. Eluvathingal TJ, Behen ME, Chugani HT, Janisse J, Bernardi B et al. 2006. Cerebellar lesions in tuberous sclerosis complex: neurobehavioral and neuroimaging correlates. J. Child Neurol. 21:846–51
     [Google Scholar]
  36. Ernst TM, Brol AE, Gratz M, Ritter C, Bingel U et al. 2019. The cerebellum is involved in processing of predictions and prediction errors in a fear conditioning paradigm. eLife 8:e46831
     [Google Scholar]
  37. Fatemi SH, Halt AR, Realmuto G, Earle J, Kist DA et al. 2002. Purkinje cell size is reduced in cerebellum of patients with autism. Cell Mol. Neurobiol. 22:171–75
     [Google Scholar]
  38. Ferrari C, Ciricugno A, Urgesi C, Cattaneo Z. 2019. Cerebellar contribution to emotional body language perception: a TMS study. Soc. Cogn. Affect. Neurosci. In press
    [Google Scholar]
  39. Ferrari C, Oldrati V, Gallucci M, Vecchi T, Cattaneo Z. 2018. The role of the cerebellum in explicit and incidental processing of facial emotional expressions: a study with transcranial magnetic stimulation. Neuroimage 169:256–64
     [Google Scholar]
  40. Forgeot d'Arc B, Devaine M, Daunizeau J. 2020. Social behavioural adaptation in autism. PLOS Comput. Biol. 16:e1007700
     [Google Scholar]
  41. Fujita H, Kodama T, du Lac S. 2020. Modular output circuits of the fastigial nucleus for diverse motor and nonmotor functions of the cerebellar vermis. eLife 9:e58613
     [Google Scholar]
  42. Gao Z, Davis C, Thomas AM, Economo MN, Abrego AM et al. 2018. A cortico-cerebellar loop for motor planning. Nature 563:113–16
     [Google Scholar]
  43. Gentsch A, Schutz-Bosbach S. 2011. I did it: unconscious expectation of sensory consequences modulates the experience of self-agency and its functional signature. J. Cogn. Neurosci. 23:3817–28
     [Google Scholar]
  44. Greene RK, Zheng S, Kinard JL, Mosner MG, Wiesen CA et al. 2019. Social and nonsocial visual prediction errors in autism spectrum disorder. Autism Res 12:878–83
     [Google Scholar]
  45. Guell X, Gabrieli JDE, Schmahmann JD. 2018. Triple representation of language, working memory, social and emotion processing in the cerebellum: convergent evidence from task and seed-based resting-state fMRI analyses in a single large cohort. Neuroimage 172:437–49
     [Google Scholar]
  46. Haith AM, Krakauer JW. 2018. The multiple effects of practice: skill, habit and reduced cognitive load. Curr. Opin. Behav. Sci. 20:196–201
     [Google Scholar]
  47. Halverson HE, Khilkevich A, Mauk MD. 2015. Relating cerebellar Purkinje cell activity to the timing and amplitude of conditioned eyelid responses. J. Neurosci. 35:7813–32
     [Google Scholar]
  48. Happé FG. 1995. The role of age and verbal ability in the theory of mind task performance of subjects with autism. Child Dev 66:843–55
     [Google Scholar]
  49. Heffley W, Hull C. 2019. Classical conditioning drives learned reward prediction signals in climbing fibers across the lateral cerebellum. eLife 8:e46764
     [Google Scholar]
  50. Heffley W, Song EY, Xu Z, Taylor BN, Hughes MA et al. 2018. Coordinated cerebellar climbing fiber activity signals learned sensorimotor predictions. Nat. Neurosci. 21:1431–41
     [Google Scholar]
  51. Heiney SA, Wohl MP, Chettih SN, Ruffolo LI, Medina JF. 2014. Cerebellar-dependent expression of motor learning during eyeblink conditioning in head-fixed mice. J. Neurosci. 34:14845–53
     [Google Scholar]
  52. Herry C, Bach DR, Esposito F, Di Salle F, Perrig WJ et al. 2007. Processing of temporal unpredictability in human and animal amygdala. J. Neurosci. 27:5958–66
     [Google Scholar]
  53. Hilton CL, Harper JD, Kueker RH, Lang AR, Abbacchi AM et al. 2010. Sensory responsiveness as a predictor of social severity in children with high functioning autism spectrum disorders. J. Autism Dev. Disord. 40:937–45
     [Google Scholar]
  54. Hoche F, Guell X, Sherman JC, Vangel MG, Schmahmann JD. 2016. Cerebellar contribution to social cognition. Cerebellum 15:732–43
     [Google Scholar]
  55. Hoffmann J, Koch I 1998. Implicit learning of loosely defined structures. Handbook of Implicit Learning MA Stadler, PA Frensch 161–99 New York: Sage Publ.
     [Google Scholar]
  56. Hull C. 2020. Prediction signals in the cerebellum: beyond supervised motor learning. eLife 9:e54073
     [Google Scholar]
  57. Igelstrom KM, Webb TW, Graziano MSA. 2017. Functional connectivity between the temporoparietal cortex and cerebellum in autism spectrum disorder. Cereb. Cortex 27:2617–27
     [Google Scholar]
  58. Imamizu H, Miyauchi S, Tamada T, Sasaki Y, Takino R et al. 2000. Human cerebellar activity reflecting an acquired internal model of a new tool. Nature 403:192–95
     [Google Scholar]
  59. Ito M. 1970. Neurophysiological aspects of the cerebellar motor control system. Int. J. Neurol. 7:162–76
     [Google Scholar]
  60. Ito M. 2008. Control of mental activities by internal models in the cerebellum. Nat. Rev. Neurosci. 9:304–13
     [Google Scholar]
  61. Ivy JW, Schreck KA. 2016. The efficacy of ABA for individuals with autism across the lifespan. Curr. Dev. Disord. Rep. 3:57–66
     [Google Scholar]
  62. Johansson F, Jirenhed DA, Rasmussen A, Zucca R, Hesslow G. 2014. Memory trace and timing mechanism localized to cerebellar Purkinje cells. PNAS 111:14930–34
     [Google Scholar]
  63. Jones RM, Somerville LH, Li J, Ruberry EJ, Libby V et al. 2011. Behavioral and neural properties of social reinforcement learning. J. Neurosci. 31:13039–45
     [Google Scholar]
  64. Kana RK, Maximo JO, Williams DL, Keller TA, Schipul SE et al. 2015. Aberrant functioning of the theory-of-mind network in children and adolescents with autism. Mol. Autism 6:59
     [Google Scholar]
  65. Kaufmann WE, Cooper KL, Mostofsky SH, Capone GT, Kates WR et al. 2003. Specificity of cerebellar vermian abnormalities in autism: a quantitative magnetic resonance imaging study. J. Child Neurol. 18:463–70
     [Google Scholar]
  66. Kawato M. 1999. Internal models for motor control and trajectory planning. Curr. Opin. Neurobiol. 9:718–27
     [Google Scholar]
  67. Kelly E, Meng F, Fujita H, Morgado F, Kazemi Y et al. 2020. Regulation of autism-relevant behaviors by cerebellar-prefrontal cortical circuits. Nat. Neurosci. 23:1102–10
     [Google Scholar]
  68. Kelly RM, Strick PL. 2003. Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate. J. Neurosci. 23:8432–44
     [Google Scholar]
  69. Kennedy DP, Adolphs R. 2012. The social brain in psychiatric and neurological disorders. Trends Cogn. Sci. 16:559–72
     [Google Scholar]
  70. Keysers C, Perrett DI. 2004. Demystifying social cognition: a Hebbian perspective. Trends Cogn. Sci. 8:501–7
     [Google Scholar]
  71. Kim JJ, Thompson RE. 1997. Cerebellar circuits and synaptic mechanisms involved in classical eyeblink conditioning. Trends Neurosci 20:177–81
     [Google Scholar]
  72. Kinard JL, Mosner MG, Greene RK, Addicott M, Bizzell J et al. 2020. Neural mechanisms of social and nonsocial reward prediction errors in adolescents with autism spectrum disorder. Autism Res 13:715–28
     [Google Scholar]
  73. Klinger LG, Klinger MR, Pohlig RL 2007. Implicit learning impairments in autism spectrum disorders. New Developments in Autism: The Future Is Today JM Perez, PM Gonzalez, ML Comi, C Nieto 76–103 Philadelphia: Jessica Kingsley Publ.
     [Google Scholar]
  74. Kloth AD, Badura A, Li A, Cherskov A, Connolly SG et al. 2015. Cerebellar associative sensory learning defects in five mouse autism models. eLife 4:e06085
     [Google Scholar]
  75. Knoblich G, Flach R. 2001. Predicting the effects of actions: interactions of perception and action. Psychol. Sci. 12:467–72
     [Google Scholar]
  76. Leekam SR, Nieto C, Libby SJ, Wing L, Gould J. 2007. Describing the sensory abnormalities of children and adults with autism. J. Autism Dev. Disord. 37:894–910
     [Google Scholar]
  77. Leiner HC, Leiner AL, Dow RS. 1991. The human cerebro-cerebellar system: its computing, cognitive, and language skills. Behav. Brain Res. 44:113–28
     [Google Scholar]
  78. Lloyd M, MacDonald M, Lord C. 2011. Motor skills of toddlers with autism spectrum disorders. Autism 17:133–46
     [Google Scholar]
  79. Locke TM, Fujita H, Hunker A, Johanson SS, Darvas M et al. 2020. Purkinje cell-specific knockout of tyrosine hydroxylase impairs cognitive behaviors. Front. Cell Neurosci. 14:228
     [Google Scholar]
  80. Locke TM, Soden ME, Miller SM, Hunker A, Knakal C et al. 2018. Dopamine D1 receptor-positive neurons in the lateral nucleus of the cerebellum contribute to cognitive behavior. Biol. Psychiatry 84:401–12
     [Google Scholar]
  81. Lupfer MB, Clark LF, Hutcherson HW. 1990. Impact of context on spontaneous trait and situational attributions. J. Personal. Soc. Psychol. 58:239–49
     [Google Scholar]
  82. Ma M, Futia GL, de Souza FMS, Ozbay BN, Llano I et al. 2020. Molecular layer interneurons in the cerebellum encode for valence in associative learning. Nat. Commun. 11:4217
     [Google Scholar]
  83. Marr D. 1969. A theory of cerebellar cortex. J. Physiol. 202:437–70
     [Google Scholar]
  84. Mazzoni P, Krakauer JW. 2006. An implicit plan overrides an explicit strategy during visuomotor adaptation. J. Neurosci. 26:3642–45
     [Google Scholar]
  85. McAfee SS, Liu Y, Sillitoe RV, Heck DH. 2019. Cerebellar lobulus simplex and Crus I differentially represent phase and phase difference of prefrontal cortical and hippocampal oscillations. Cell Rep 27:2328–34.e3
     [Google Scholar]
  86. Medina JF, Garcia KS, Nores WL, Taylor NM, Mauk MD. 2000. Timing mechanisms in the cerebellum: testing predictions of a large-scale computer simulation. J. Neurosci. 20:5516–25
     [Google Scholar]
  87. Menashe I, Grange P, Larsen EC, Banerjee-Basu S, Mitra PP 2013. Co-expression profiling of autism genes in the mouse brain. PLOS Comput. Biol. 9:e1003128
     [Google Scholar]
  88. Miall RC, Christensen LO, Cain O, Stanley J 2007. Disruption of state estimation in the human lateral cerebellum. PLOS Biol 5:e316
     [Google Scholar]
  89. Molenberghs P, Cunnington R, Mattingley JB. 2012. Brain regions with mirror properties: a meta-analysis of 125 human fMRI studies. Neurosci. Biobehav. Rev. 36:341–49
     [Google Scholar]
  90. Mosconi MW, Wang Z, Schmitt LM, Tsai P, Sweeney JA. 2015. The role of cerebellar circuitry alterations in the pathophysiology of autism spectrum disorders. Front. Neurosci. 9:296
     [Google Scholar]
  91. Nelson SB, Valakh V. 2015. Excitatory/inhibitory balance and circuit homeostasis in autism spectrum disorders. Neuron 87:684–98
     [Google Scholar]
  92. Ohmae S, Medina JF. 2015. Climbing fibers encode a temporal-difference prediction error during cerebellar learning in mice. Nat. Neurosci. 18:1798–803
     [Google Scholar]
  93. Palay SL, Chan-Palay V. 2012. Cerebellar Cortex: Cytology and Organization Berlin: Springer
  94. Parker KL, Kim YC, Kelley RM, Nessler AJ, Chen KH et al. 2017. Delta-frequency stimulation of cerebellar projections can compensate for schizophrenia-related medial frontal dysfunction. Mol. Psychiatry 22:647–55
     [Google Scholar]
  95. Pellicano E, Burr D. 2012. When the world becomes ‘too real’: a Bayesian explanation of autistic perception. Trends Cogn. Sci. 16:504–10
     [Google Scholar]
  96. Pellicano E, Jeffery L, Burr D, Rhodes G. 2007. Abnormal adaptive face-coding mechanisms in children with autism spectrum disorder. Curr. Biol. 17:1508–12
     [Google Scholar]
  97. Person AL, Raman IM. 2012. Purkinje neuron synchrony elicits time-locked spiking in the cerebellar nuclei. Nature 481:502–5
     [Google Scholar]
  98. Peter S, ten Brinke MM, Stedehouder J, Reinelt CM, Wu B et al. 2016. Dysfunctional cerebellar Purkinje cells contribute to autism-like behaviour in Shank2-deficient mice. Nat. Commun. 7:12627
     [Google Scholar]
  99. Piochon C, Kloth AD, Grasselli G, Titley HK, Nakayama H et al. 2014. Cerebellar plasticity and motor learning deficits in a copy-number variation mouse model of autism. Nat. Commun. 5:5586
     [Google Scholar]
  100. Plutchik R. 1959. The effects of high intensity intermittent sound on performance, feeling, and physiology. Psychol. Bull. 56:133–51
     [Google Scholar]
  101. Popa LS, Ebner TJ. 2018. Cerebellum, predictions and errors. Front. . Cell Neurosci 12:524
     [Google Scholar]
  102. Prestori F, Mapelli L, D'Angelo E. 2019. Diverse neuron properties and complex network dynamics in the cerebellar cortical inhibitory circuit. Front. Mol. Neurosci. 12:267
     [Google Scholar]
  103. Proville RD, Spolidoro M, Guyon N, Dugue GP, Selimi F et al. 2014. Cerebellum involvement in cortical sensorimotor circuits for the control of voluntary movements. Nat. Neurosci. 17:1233–39
     [Google Scholar]
  104. Raymond JL, Medina JF. 2018. Computational principles of supervised learning in the cerebellum. Annu. Rev. Neurosci. 41:233–53
     [Google Scholar]
  105. Reith RM, McKenna J, Wu H, Hashmi SS, Cho S-H et al. 2013. Loss of Tsc2 in Purkinje cells is associated with autistic-like behavior in a mouse model of tuberous sclerosis complex. Neurobiol. Dis. 51:93–103
     [Google Scholar]
  106. Rushworth MF, Mars RB, Summerfield C. 2009. General mechanisms for making decisions?. Curr. Opin. Neurobiol. 19:75–83
     [Google Scholar]
  107. Ryu YH, Lee JD, Yoon PH, Kim DI, Lee HB, Shin YJ. 1999. Perfusion impairments in infantile autism on technetium-99m ethyl cysteinate dimer brain single-photon emission tomography: comparison with findings on magnetic resonance imaging. Eur. J. Nucl. Med. 26:253–59
     [Google Scholar]
  108. Sakai K. 2008. Task set and prefrontal cortex. Annu. Rev. Neurosci. 31:219–45
     [Google Scholar]
  109. Schlerf J, Ivry RB, Diedrichsen J. 2012. Encoding of sensory prediction errors in the human cerebellum. J. Neurosci. 32:4913–22
     [Google Scholar]
  110. Schmahmann JD, Guell X, Stoodley CJ, Halko MA. 2019. The theory and neuroscience of cerebellar cognition. Annu. Rev. Neurosci. 42:337–64
     [Google Scholar]
  111. Schmahmann JD, Weilburg JB, Sherman JC. 2007. The neuropsychiatry of the cerebellum—insights from the clinic. Cerebellum 6:254–67
     [Google Scholar]
  112. Schmolesky MT, Wang Y, Hanes DP, Thompson KG, Leutgeb S et al. 1998. Signal timing across the macaque visual system. J. Neurophysiol. 79:3272–78
     [Google Scholar]
  113. Schultz W, Dickinson A. 2000. Neuronal coding of prediction errors. Annu. Rev. Neurosci. 23:473–500
     [Google Scholar]
  114. Sears LL, Finn PR, Steinmetz JE. 1994. Abnormal classical eye-blink conditioning in autism. J. Autism Dev. Disord. 24:737–51
     [Google Scholar]
  115. Sebanz N, Knoblich G. 2009. Prediction in joint action: what, when, and where. Top. Cogn. Sci. 1:353–67
     [Google Scholar]
  116. Shadmehr R, Smith MA, Krakauer JW. 2010. Error correction, sensory prediction, and adaptation in motor control. Annu. Rev. Neurosci. 33:89–108
     [Google Scholar]
  117. Siciliano L, Clausi S. 2020. Implicit versus explicit emotion processing in autism spectrum disorders: an opinion on the role of the cerebellum. Front. Psychol. 11:96
     [Google Scholar]
  118. Sinha P, Kjelgaard MM, Gandhi TK, Tsourides K, Cardinaux AL et al. 2014. Autism as a disorder of prediction. PNAS 111:15220–25
     [Google Scholar]
  119. Sivaswamy L, Kumar A, Rajan D, Behen M, Muzik O et al. 2010. A diffusion tensor imaging study of the cerebellar pathways in children with autism spectrum disorder. J. Child Neurol. 25:1223–31
     [Google Scholar]
  120. Sokolov AA. 2018. The cerebellum in social cognition. Front. Cell. Neurosci. 12:145
     [Google Scholar]
  121. Sokolov AA, Gharabaghi A, Tatagiba MS, Pavlova M. 2010. Cerebellar engagement in an action observation network. Cereb. Cortex 20:486–91
     [Google Scholar]
  122. Sokolov AA, Miall RC, Ivry RB. 2017. The cerebellum: adaptive prediction for movement and cognition. Trends Cogn. Sci. 21:313–32
     [Google Scholar]
  123. Stanfield AC, Philip RCM, Whalley H, Romaniuk L, Hall J et al. 2017. Dissociation of brain activation in autism and schizotypal personality disorder during social judgments. Schizophr. Bull. 43:1220–28
     [Google Scholar]
  124. Stoodley CJ. 2014. Distinct regions of the cerebellum show gray matter decreases in autism, ADHD, and developmental dyslexia. Front. Syst. Neurosci. 8:92
     [Google Scholar]
  125. Stoodley CJ. 2016. The cerebellum and neurodevelopmental disorders. Cerebellum 15:34–37
     [Google Scholar]
  126. Stoodley CJ, D'Mello AM, Ellegood J, Jakkamsetti V, Liu P et al. 2017. Altered cerebellar connectivity in autism and cerebellar-mediated rescue of autism-related behaviors in mice. Nat. Neurosci. 20:1744–51
     [Google Scholar]
  127. Stoodley CJ, Limperopoulos C. 2016. Structure–function relationships in the developing cerebellum: evidence from early-life cerebellar injury and neurodevelopmental disorders. Semin. Fetal Neonatal Med. 21:356–64
     [Google Scholar]
  128. Stoodley CJ, Schmahmann JD. 2010. Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing. Cortex 46:831–44
     [Google Scholar]
  129. Taylor JA, Krakauer JW, Ivry RB. 2014. Explicit and implicit contributions to learning in a sensorimotor adaptation task. J. Neurosci. 34:3023–32
     [Google Scholar]
  130. Teufel C, Fletcher PC, Davis G 2010. Seeing other minds: attributed mental states influence perception. Trends Cogn. Sci. 14:376–82
     [Google Scholar]
  131. Therrien AS, Bastian AJ. 2015. Cerebellar damage impairs internal predictions for sensory and motor function. Curr. Opin. Neurobiol. 33:127–33
     [Google Scholar]
  132. Todd AR, Molden DC, Ham J, Vonk R. 2011. The automatic and co-occurring activation of multiple social inferences. J. Exp. Soc. Psychol. 47:37–49
     [Google Scholar]
  133. Tsai PT, Hull C, Chu Y, Greene-Colozzi E, Sadowski AR et al. 2012. Autistic-like behaviour and cerebellar dysfunction in Purkinje cell Tsc1 mutant mice. Nature 488:647–51
     [Google Scholar]
  134. Tsai PT, Rudolph S, Guo C, Ellegood J, Gibson JM et al. 2018. Sensitive periods for cerebellar-mediated autistic-like behaviors. Cell Rep 25:357–67.e4
     [Google Scholar]
  135. Tseng YW, Diedrichsen J, Krakauer JW, Shadmehr R, Bastian AJ. 2007. Sensory prediction errors drive cerebellum-dependent adaptation of reaching. J. Neurophysiol. 98:54–62
     [Google Scholar]
  136. Van de Cruys S, Evers K, Van der Hallen R, Van Eylen L, Boets B et al. 2014. Precise minds in uncertain worlds: predictive coding in autism. Psychol. Rev. 121:649–75
     [Google Scholar]
  137. Van Eylen L, Boets B, Steyaert J, Evers K, Wagemans J, Noens I. 2011. Cognitive flexibility in autism spectrum disorder: explaining the inconsistencies?. Res. Autism Spectr. Disord. 5:1390–401
     [Google Scholar]
  138. Van Overwalle F, Baetens K, Marien P, Vandekerckhove M. 2014. Social cognition and the cerebellum: a meta-analysis of over 350 fMRI studies. Neuroimage 86:554–72
     [Google Scholar]
  139. Van Overwalle F, Manto M, Cattaneo Z, Clausi S, Ferrari C et al. 2020. Consensus paper: cerebellum and social cognition. Cerebellum 19:833–68
     [Google Scholar]
  140. Verly M, Verhoeven J, Zink I, Mantini D, Peeters R et al. 2014. Altered functional connectivity of the language network in ASD: role of classical language areas and cerebellum. NeuroImage Clin 4:374–82
     [Google Scholar]
  141. Volpe JJ. 2009. Cerebellum of the premature infant: rapidly developing, vulnerable, clinically important. J. Child Neurol. 24:1085–104
     [Google Scholar]
  142. Wagner MJ, Kim TH, Savall J, Schnitzer MJ, Luo L. 2017. Cerebellar granule cells encode the expectation of reward. Nature 544:96–100
     [Google Scholar]
  143. Wang AT, Lee SS, Sigman M, Dapretto M. 2007. Reading affect in the face and voice: neural correlates of interpreting communicative intent in children and adolescents with autism spectrum disorders. Arch. Gen. Psychiatry 64:698–708
     [Google Scholar]
  144. Wang SS-H, Kloth AD, Badura A. 2014. The cerebellum, sensitive periods, and autism. Neuron 83:518–32
     [Google Scholar]
  145. Whitney ER, Kemper TL, Bauman ML, Rosene DL, Blatt GJ. 2008. Cerebellar Purkinje cells are reduced in a subpopulation of autistic brains: a stereological experiment using calbindin-D28k. Cerebellum 7:406–16
     [Google Scholar]
  146. Whitney ER, Kemper TL, Rosene DL, Bauman ML, Blatt GJ. 2009. Density of cerebellar basket and stellate cells in autism: evidence for a late developmental loss of Purkinje cells. J. Neurosci. Res. 87:2245–54
     [Google Scholar]
  147. Wolpert DM, Flanagan JR. 2001. Motor prediction. Curr. Biol. 11:R729–32
     [Google Scholar]
  148. Wolpert DM, Miall RC. 1996. Forward models for physiological motor control. Neural Netw 9:1265–79
     [Google Scholar]
  149. Wolpert DM, Miall RC, Kawato M. 1998. Internal models in the cerebellum. Trends Cogn. Sci. 2:338–47
     [Google Scholar]
  150. Yamamoto K, Kawato M, Kotosaka S, Kitazawa S. 2007. Encoding of movement dynamics by Purkinje cell simple spike activity during fast arm movements under resistive and assistive force fields. J. Neurophysiol. 97:1588–99
     [Google Scholar]
  151. Yomogida Y, Sugiura M, Sassa Y, Wakusawa K, Sekiguchi A et al. 2010. The neural basis of agency: an fMRI study. Neuroimage 50:198–207
     [Google Scholar]
/content/journals/10.1146/annurev-neuro-100120-092143
Loading
Adaptive Prediction for Social Contexts: The Cerebellar Contribution to Typical and Atypical Social Behaviors
Annual Review of Neuroscience 44, 475 (2021); https://doi.org/10.1146/annurev-neuro-100120-092143
/content/journals/10.1146/annurev-neuro-100120-092143
/content/journals/10.1146/annurev-neuro-100120-092143
Loading

Data & Media loading...

  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error