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What is mood? A computational perspective
Open accessAbstract
The neurobiological understanding of mood, and by extension mood disorders, remains elusive despite decades of research implicating several neuromodulator systems. This review considers a new approach based on existing theories of functional brain organisation. The free energy principle (a.k.a. active inference), and its instantiation in the Bayesian brain, offers a complete and simple formulation of mood. It has been proposed that emotions reflect the precision of - or certainty about - the predicted sensorimotor/interoceptive consequences of action. By extending this reasoning, in a hierarchical setting, we suggest mood states act as (hyper) priors over uncertainty (i.e. emotions). Here, we consider the same computational pathology in the proprioceptive and interoceptive (behavioural and autonomic) domain in order to furnish an explanation for mood disorders. This formulation reconciles several strands of research at multiple levels of enquiry.
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“High-level priors constraining more domain-general affective states such as mood (Clark et al. 2018) would also be relaxed under the REBUS model.”
From Consciousness in active inference: Deep self-models, other minds, and the challenge of psychedelic-induced ego-dissolution (2021) · cites this paper as Clark et al. 2018
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“…hypotheses propose that the neurobiological underpinnings of a variety of disorders arise from structural or functional abnormalities in the brain consequent on a combination of environmental stress and genetic vulnerabilities (Videbech & Ravnkilde, 2004; Ota & Duman, 2013; Duman, 2014).”
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BackgroundInfluentialUsing Attentional Bias Modification as a Cognitive Vaccine Against Depression
Browning, M., Holmes, E. A., Charles, M., Cowen, P. J., & Harmer, C. J. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.04.014 · Cited by 197 · cited 2×
“2009; Harmer & Cowen, 2013) and correspondingly that modulating attentional bias can provide therapeutic benefit (Browning et al. 2012).”
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“…al. have thus proposed that a negative emotional bias is a core feature of depression and is the psychological target of antidepressant medication (Harmer et al. 2009; Harmer & Cowen, 2013) and correspondingly that modulating attentional bias can provide therapeutic benefit (Browning et al. 2012).”
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Badcock, P. B., Davey, C. G., Whittle, S., Allen, N. B., & Friston, K. J. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.01.005 · Cited by 190 · cited 1×
“A corollary of this is that patients with low mood (low prior precision) should show a hypersensitivity to interoceptive cues (high sensory precision) and a failure of sensory attenuation (Badcock et al. 2017) – of the sort associated with stress responses (please see below).”
BackgroundTowards a genuinely medical model for psychiatric nosology
Nesse, R. M., & Stein, D. J. (2012) · BMC Medicine · doi:10.1186/1741-7015-10-5 · Cited by 166
Schlösser, R. G. M., Wagner, G., Koch, K., Dahnke, R., Reichenbach, J. R., & Sauer, H. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.08.002 · Cited by 154 · cited 2×
“…this regard (Friston et al. 2003) and could prove a fruitful tool for further investigation – specifically in examining the task-dependent coupling between hierarchical levels of neuromodula-tor control (Schlosser et al. 2008; Lu et al. 2012; Radaelli et al. 2015; Vai et al. 2015; Vai et al. 2016).”
BackgroundMethodRisk and risk prediction error signals in anterior insula
Bossaerts, P. L. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0253-1 · Cited by 152 · cited 1×
“Similarly, it has been shown that signal change in the anterior insula is significantly related to the magnitude of prediction error (Bossaerts, 2010).”
BackgroundSladky, R., Höflich, A., Küblböck, M., Kraus, C., Baldinger, P., Moser, E., Lanzenberger, R., & Windischberger, C. (2015) · Cerebral Cortex · doi:10.1093/cercor/bht279 · Cited by 152 · cited 1×
“…increased activation in orbitofrontal cortex and amygdala when viewing emotional faces (Sladky et al. 2012), but furthermore, in controls this network shows top-down modulation – which is reversed in patients – orbitofrontal cortex drives greater activation in amygdala (Sladky et al. 2015).”
BackgroundStress risk factors and stress-related pathology: Neuroplasticity, epigenetics and endophenotypes
Radley, J. J., Kabbaj, M., Jacobson, L., Heydendael, W., Yehuda, R., & Herman, J. P. (2011) · Stress · doi:10.3109/10253890.2011.604751 · Cited by 147 · cited 1×
“Although speculative, this provides a potential framework that can be modelled in terms of active inference and is entirely consistent with theories based upon allostasis (McEwen, 2000; Radley et al. 2011; Braithwaite et al. 2015).”
ResultLu, Q., Li, H., Luo, G., Wang, Y., Tang, H., Han, L., & Yao, Z. (2012) · Neuroscience Letters · doi:10.1016/j.neulet.2012.06.058 · Cited by 129 · cited 2×
“…this regard (Friston et al. 2003) and could prove a fruitful tool for further investigation – specifically in examining the task-dependent coupling between hierarchical levels of neuromodula-tor control (Schlosser et al. 2008; Lu et al. 2012; Radaelli et al. 2015; Vai et al. 2015; Vai et al. 2016).”
BackgroundMethodDissociable Effects of Serotonin and Dopamine on the Valuation of Harm in Moral Decision Making
Crockett, M. J., Siegel, J. Z., Kurth-Nelson, Z. L., Ousdal, O. T., Story, G. W., Frieband, C., Grosse-Rueskamp, J. M., Dayan, P., & Dolan, R. J. (2015) · Current Biology · doi:10.1016/j.cub.2015.05.021 · Cited by 124 · cited 2×
“D, depression; M, Mania; Ax, anxious depression. harm-aversion, while levodopa made individuals more likely to harm themselves than others (Crockett et al. 2015).”
BackgroundSullivan, T. P., Fehon, D. C., Andrés-Hyman, R. C., Lipschitz, D. S., & Grilo, C. M. (2006) · Journal of Traumatic Stress · doi:10.1002/jts.20092 · Cited by 122 · cited 1×
“This is perhaps best exemplified by the risk posed for PTSD by acute and extreme episodes of trauma (Sullivan et al. 2006).”
BackgroundChildhood trauma in bipolar disorder
Watson, S., Gallagher, P., Dougall, D., Porter, R., Moncrieff, J., Ferrier, I. N., & Young, A. H. (2014) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867413516681 · Cited by 122 · cited 2×
“This accords with the findings from recent studies (Watson et al. 2014) though not others.”
ResultSelf-citationvan der Gucht, E., Morriss, R. K., Lancaster, G., Kinderman, P., & Bentall, R. P. (2009) · The British Journal of Psychiatry · doi:10.1192/bjp.bp.107.047894 · Cited by 113 · cited 1×
“This has been demonstrated using self-report measures of behavioural drive (Van der Gucht et al. 2009) and response time analyses to financial reward cues (Singh et al. 2013).”
MethodAre computational models of any use to psychiatry?
Huys, Q. J. M., Moutoussis, M., & Williams, J. H. (2011) · Neural Networks · doi:10.1016/j.neunet.2011.03.001 · Cited by 106 · cited 2×
“…trials (Chekroud, 2015) and represents a potentially important approach; however, it may be possible to go one step further and replace the search for a biomarker with a computational signature (Nitsche et al. 2010; Huys et al. 2011; Barch et al. 2012; Montague et al. 2012; Wang & Krystal, 2014).”
BackgroundFronto-limbic disconnection in bipolar disorder
Radaelli, D., Papa, G. S., Vai, B., Poletti, S., Smeraldi, E., Colombo, C., & Benedetti, F. (2014) · European Psychiatry · doi:10.1016/j.eurpsy.2014.04.001 · Cited by 106 · cited 4×
“…this regard (Friston et al. 2003) and could prove a fruitful tool for further investigation – specifically in examining the task-dependent coupling between hierarchical levels of neuromodula-tor control (Schlosser et al. 2008; Lu et al. 2012; Radaelli et al. 2015; Vai et al. 2015; Vai et al. 2016).”
BackgroundMethodInfluentialComputational psychiatry: a Rosetta Stone linking the brain to mental illness
Corlett, P. R., & Fletcher, P. C. (2014) · The Lancet Psychiatry · doi:10.1016/s2215-0366(14)70298-6 · Cited by 105 · cited 1×
“However, modern accounts of brain function reject the classical notion of the brain as a passive organ in favour of theories of embodiment and self-organisation (Friston, 2010; Seth, 2013; Corlett & Fletcher, 2014).”
BackgroundMood Instability and Reward Dysregulation—A Neurocomputational Model of Bipolar Disorder
Mason, L., Eldar, E., & Rutledge, R. B. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.3163 · Cited by 100 · cited 1×
“Accordingly, manic individuals lose the capacity to appreciate the unpredictable consequences of their actions and will engage in overconfident, high-risk behaviours (Mason et al. 2017).”
BackgroundReward Processing in Adolescents With Bipolar I Disorder
Singh, M. K., Chang, K., Kelley, R. G., Cui, X., Sherdell, L., Howe, M. E., Gotlib, I. H., & Reiss, A. L. (2012) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2012.10.004 · Cited by 97 · cited 2×
“This has been demonstrated using self-report measures of behavioural drive (Van der Gucht et al. 2009) and response time analyses to financial reward cues (Singh et al. 2013).”
BackgroundMethodOta, K. T., & Duman, R. S. (2013) · Neurobiology of Disease · doi:10.1016/j.nbd.2012.05.022 · Cited by 94 · cited 1×
“…hypotheses propose that the neurobiological underpinnings of a variety of disorders arise from structural or functional abnormalities in the brain consequent on a combination of environmental stress and genetic vulnerabilities (Videbech & Ravnkilde, 2004; Ota & Duman, 2013; Duman, 2014).”
BackgroundSladky, R., Höflich, A., Atanelov, J., Kraus, C., Baldinger, P., Moser, E., Lanzenberger, R., & Windischberger, C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0050050 · Cited by 85 · cited 2×
“showed that patients with social anxiety disorder demonstrated increased activation in orbitofrontal cortex and amygdala when viewing emotional faces (Sladky et al. 2012), but furthermore, in controls this network shows top-down modulation – which is reversed in patients – orbitofrontal cortex drives greater activatio…”
BackgroundThe Clinical Translation of a Measure of Gain Control: The Contrast-Contrast Effect Task
Barch, D. M., Carter, C. S., Dakin, S. C., Gold, J. M., Luck, S. J., MacDonald, A. W., Ragland, J. D., Silverstein, S. M., & Strauss, M. E. (2011) · Schizophrenia Bulletin · doi:10.1093/schbul/sbr154 · Cited by 85 · cited 2×
“…trials (Chekroud, 2015) and represents a potentially important approach; however, it may be possible to go one step further and replace the search for a biomarker with a computational signature (Nitsche et al. 2010; Huys et al. 2011; Barch et al. 2012; Montague et al. 2012; Wang & Krystal, 2014).”
BackgroundDynamic causal modelling of precision and synaptic gain in visual perception — an EEG study
Brown, H. R., & Friston, K. J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.044 · Cited by 84 · cited 1×
“This ties emotional states to the resolution of uncertainty and, through the biophysical encoding of precision, to neuromodulation and cortical gain control (Brown & Friston, 2012).”
BackgroundAn Active Inference view of cognitive control
Pezzulo, G. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00478 · Cited by 68 · cited 2×
“The active minimisation of free energy is known as active inference , which means the brain can selectively sample from data that concur with its current expectations (Friston et al. 2011; Pezzulo, 2012).”
BackgroundVai, B., Bulgarelli, C., Godlewska, B. R., Cowen, P. J., Benedetti, F., & Harmer, C. J. (2016) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2016.09.640 · Cited by 65
Early life trauma, depression and the glucocorticoid receptor gene—An epigenetic perspective
Smart, C., Strathdee, G., Watson, S., Murgatroyd, C., & McAllister-Williams, R. H. (2015) · Psychological Medicine · doi:10.1017/s0033291715001555 · Cited by 61 · cited 1×
“Epigenetics has emerged as a major field of enquiry in recent years, specifically in relation to methylation of the NR3C1 gene, which encodes GR (Nantharat et al. 2015; Smart et al. 2015; Palma-Gudiel et al. 2016).”
BackgroundThe virtual bodily self: Mentalisation of the body as revealed in anosognosia for hemiplegia
Fotopoulou, A. (2014) · Consciousness and Cognition · doi:10.1016/j.concog.2014.09.018 · Cited by 55 · cited 1×
“We argue that progress may be facilitated by an appreciation of the dynamic and selforganising nature of neurobiological systems (Seth, 2013; Fotopoulou, 2015; Clark et al. 2016).”
BackgroundUnifying treatments for depression: an application of the free energy principle
Chekroud, A. M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00153 · Cited by 55 · cited 3×
“One recent and novel study has employed machine-learning techniques to predict treatment outcome in clinical trials (Chekroud, 2015) and represents a potentially important approach; however, it may be possible to go one step further and replace the search for a biomarker with a computational signature (Nitsche et al.”
BackgroundInfluentialComputational Psychiatry and the Challenge of Schizophrenia
Krystal, J. H., Murray, J. D., Chekroud, A. M., Corlett, P. R., Yang, G., Wang, X., & Anticevic, A. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx025 · Cited by 49 · cited 1×
“This notion has gained traction as an explanation for autism and schizophrenia in the exteroceptive (perceptual) domain (Lawson et al. 2014; Corlett, 2017; Krystal et al. 2017).”
BackgroundNantharat, M., Wanitchanon, T., Amesbutr, M., Tammachote, R., & Praphanphoj, V. (2015) · Genetics and Molecular Research · doi:10.4238/2015.december.29.15 · Cited by 46 · cited 1×
“Epigenetics has emerged as a major field of enquiry in recent years, specifically in relation to methylation of the NR3C1 gene, which encodes GR (Nantharat et al. 2015; Smart et al. 2015; Palma-Gudiel et al. 2016).”
BackgroundVai, B., Poletti, S., Radaelli, D., Dallaspezia, S., Bulgarelli, C., Locatelli, C., Bollettini, I., Falini, A., Colombo, C., Smeraldi, E., et al. (2015) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2015.07.015 · Cited by 42 · cited 2×
“…this regard (Friston et al. 2003) and could prove a fruitful tool for further investigation – specifically in examining the task-dependent coupling between hierarchical levels of neuromodula-tor control (Schlosser et al. 2008; Lu et al. 2012; Radaelli et al. 2015; Vai et al. 2015; Vai et al. 2016).”
BackgroundMethodPerturbed reward processing in pediatric bipolar disorder: an antisaccade study
Mueller, S. C., Ng, P., Temple, V., Hardin, M. G., Pine, D. S., Leibenluft, E., & Ernst, M. (2010) · Journal of Psychopharmacology · doi:10.1177/0269881109353462 · Cited by 42 · cited 1×
“Accordingly patients also show a failure to learn from punishing cues (Mueller et al. 2010).”
BackgroundValiengo, L. L., Soeiro-de-Souza, M. G., Marques, A. H., Moreno, D. H., Juruena, M. F., Andreazza, A. C., Gattaz, W. F., & Machado-Vieira, R. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.11.046 · Cited by 36 · cited 1×
“Mania is less well studied but there are reports of underactive HPA axis drive being particularly related to euphoria (Valiengo et al. 2012).”
BackgroundDopaminergic Impact on Cortical Excitability in Humans
Nitsche, M. A., Monte-Silva, K. K., Kuo, M., & Paulus, W. (2010) · Reviews in the Neurosciences · doi:10.1515/revneuro.2010.21.4.289 · Cited by 36 · cited 2×
“…trials (Chekroud, 2015) and represents a potentially important approach; however, it may be possible to go one step further and replace the search for a biomarker with a computational signature (Nitsche et al. 2010; Huys et al. 2011; Barch et al. 2012; Montague et al. 2012; Wang & Krystal, 2014).”
BackgroundGao, S., Klomp, A., Wu, J., Swaab, D. F., & Bao, A. (2013) · Journal of Affective Disorders · doi:10.1016/j.jad.2012.12.003 · Cited by 33 · cited 1×
“In depression there is increased paraventricular nucleus (PVN) drive and CRH production (Raadsheer et al. 1994; Gao et al. 2013) and resistance to glucocorticoid receptor (GR) mediated negative feed-back (Holsboer et al. 1982; Sher et al. 2013).”
BackgroundSher, L., Oquendo, M. A., Burke, A. K., Cooper, T. B., & Mann, J. J. (2013) · Journal of Affective Disorders · doi:10.1016/j.jad.2013.06.049 · Cited by 30 · cited 2×
“2013) and resistance to glucocorticoid receptor (GR) mediated negative feedback (Holsboer et al. 1982; Sher et al. 2013).”
BackgroundThe aetiopathogenesis of fatigue: unpredictable, complex and persistent
Clark, J. E., Ng, W., Watson, S., & Newton, J. L. (2016) · British Medical Bulletin · doi:10.1093/bmb/ldv057 · Cited by 20 · cited 1×
“We argue that progress may be facilitated by an appreciation of the dynamic and selforganising nature of neurobiological systems (Seth, 2013; Fotopoulou, 2015; Clark et al. 2016).”
BackgroundI Predict, Therefore I Am: Perturbed Predictive Coding Under Ketamine and in Schizophrenia
Corlett, P. R. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.12.007 · Cited by 12 · cited 1×
“This notion has gained traction as an explanation for autism and schizophrenia in the exteroceptive (perceptual) domain (Lawson et al. 2014; Corlett, 2017; Krystal et al. 2017).”
BackgroundPalma‐Gudiel, H., Córdova‐Palomera, A., Marqués-Feixa, L., Miquel, F. C., & Fañanás, L. (2016) · European Psychiatry · doi:10.1016/j.eurpsy.2016.01.025 · Cited by 2 · cited 1×
“Epigenetics has emerged as a major field of enquiry in recent years, specifically in relation to methylation of the NR3C1 gene, which encodes GR (Nantharat et al. 2015; Smart et al. 2015; Palma-Gudiel et al. 2016).”
Background
Cited by
Sorted by citations
REBUS and the anarchic brain: Toward a unified model of the brain action of psychedelics
Carhart-Harris, R. L., & Friston, K. J. (2019) · Pharmacological Reviews · doi:10.1124/pr.118.017160 · Cited by 1,180
“We also propose that these pathologic beliefs are ascribed excessive precision, weight, or influence in many psychiatric disorders (Clark et al., 2018).”
BackgroundBeing a Beast Machine: The Somatic Basis of Selfhood
Seth, A. K., & Tsakiris, M. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.08.008 · Cited by 371
“Clark and colleagues similarly emphasize precision, associating major depression with being certain about encountering uncertain environments, thereby precluding effective allostatic regulation [83].”
Emotion words, emotion concepts, and emotional development in children: A constructionist hypothesis
Hoemann, K., Xu, F., & Barrett, L. F. (2019) · Developmental Psychology · doi:10.1037/dev0000686 · Cited by 354
A step-by-step tutorial on active inference and its application to empirical data
Smith, R., Friston, K. J., & Whyte, C. J. (2022) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2021.102632 · Cited by 246
Deeply Felt Affect: The Emergence of Valence in Deep Active Inference
Hesp, C., Smith, R., Parr, T., Allen, M., Friston, K. J., & Ramstead, M. J. D. (2021) · Neural Computation · doi:10.1162/neco_a_01341 · Cited by 246
“In other contexts, it has been suggested that action model precision updates (what we have labeled AC ) could be used to inform selective attention (e.g., Clark et al., 2018; Palacios, Razi, Parr, Kirchhoff, & Friston, 2019).”
BackgroundSelf-citation
Metadata
- Authors
- Clark, J. E., Watson, S., & Friston, K. J.
- Affiliations
- Newcastle University (GB)
- Cumbria Northumberland Tyne and Wear NHS Foundation Trust (GB)
- University College London (GB)
- Corresponding author
- Clark, James E
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2018-02-26
- Volume
- 48
- Issue
- 14
- Pages
- 2277-2284
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- PMC
- PMC6340107
- OpenAlex
- W2789154098
- Cited by
- 204
- References
- 104
- Citations by year
- 2026: 21 · 2025: 28 · 2024: 21 · 2023: 36 · 2022: 34 · 2021: 21 · 2020: 23 · 2019: 17 · 2018: 3
- FWCI
- 2.14
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Psychological Medicine (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity) (cc-by)
- Funders
- Wellcome Trust (088130, 088130/Z/09/Z)
- National Institute for Health and Care Research
- Newcastle University
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- mood, mood disorders, free energy principle, active inference, Bayesian brain, emotions, interoception, proprioception, uncertainty, hyperprior, computational psychiatry
- MeSH terms
- Affect, Brain, Humans, Models, Theoretical, Mood Disorders
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