Abstract
This chapter reviews current perspectives on the neural basis of subjective experience. Its primary focus is on the interaction between two broad dimensions of experience: subjective contents (e.g., the conscious experience of seeing a red ball or feeling a sharp pain) and the global brain states that modulate the representation of those contents and how they evolve over time (e.g., moods, dreaming, and vigilance). The neural basis of these two aspects of experience will be discussed across multiple levels of description, including large-scale network, neurocomputational, and cellular-level perspectives. When integrated, these perspectives highlight the way that small-scale neuronal circuits may be interconnected so as to implement a hierarchical computational system for inferring the probability that various states of the world (including the body), at various levels of description, have caused the sensory input that has been received. Emotional experience is used to provide an in-depth example of the complex interactions within this type of system that are necessary to account for this phenomenon. The chapter next turns to the role of global brain states in modulating the contents of experience – including mood, sleep/dreaming, and other altered states of consciousness. Global brain states are linked to the broad influence of neuromodulators and the way they can alter neurocomputational inference processes by either amplifying or attenuating the relative influence of prior expectations and sensory input on experience. Different global brain states are then associated with different patterns of modulatory influence on neuronal populations encoding different types of prior expectations at different levels of hierarchical processing. This chapter also briefly considers the potential clinical relevance of understanding the neural basis of what contents do and do not become consciously accessible, and the vulnerabilities of such a system for transitioning into maladaptive states. This chapter ends by highlighting the nascent state of the field of consciousness research and the importance of an interdisciplinary, multilevel approach to understanding this important topic.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
In research on consciousness, a related distinction is sometimes made between the transitive and intransitive uses of the term “conscious” (Dehaene and Changeux 2011). The former use corresponds closely to the use of the term “conscious contents” in this chapter (e.g., “I was not conscious of my change in heart rate”). The latter use instead corresponds to the range of “global states” (i.e., as the term is used in this chapter) that range from complete unconsciousness (e.g., “I was unconscious for 3 hours after the accident”) to states of high vigilance/alertness.
- 2.
Adaptive behavior can be understood from a number of vantage points. For example, from an evolutionary perspective, it could be understood as behavior that, on average, promotes the survival of an organism for long enough to reproduce within its ecological niche (i.e., the environment within which its behavioral dispositions were naturally selected for over evolutionary time). From a personal perspective, it could also be viewed as behavior that aids an organism in fulfilling its own needs, goals, and desires. Such vantage points need not always agree, however; thus, the definition of “adaptive” can at times be problematic – with one definition being more appropriate than the other in different contexts (e.g., in the discussion of automatic affective responses below, the evolutionary definition may be more appropriate when the two vantage points disagree).
- 3.
It is important to note that this idea has been (and to some degree remains) controversial. This will be expanded on within the section on “Open Questions” later in the chapter.
- 4.
This could represent an example of metaplasticity – the ability to control the plasticity of other synaptic connections that implement learning.
- 5.
In line with this, there is also relatively strong delta activity during coma.
- 6.
For more details on plasticity mechanisms, see (7 Chap. 7) in this volume.
References
Ackermann S, Rasch B (2014) Differential effects of non-REM and REM sleep on memory consolidation? Curr Neurol Neurosci Rep 14:430. https://doi.org/10.1007/s11910-013-0430-8
Adams R, Perrinet L, Friston K (2012) Smooth pursuit and visual occlusion: active inference and oculomotor control in schizophrenia. PLoS One 7:e47502. https://doi.org/10.1371/journal.pone.0047502
Anderson M (2014) After phrenology: neural reuse and the interactive brain. MIT Press, Cambridge
Aviezer H, Hassin R, Ryan J, Grady C, Susskind J, Anderson A et al (2008) Angry, disgusted, or afraid? Psychol Sci 19:724–732. https://doi.org/10.1111/j.1467-9280.2008.02148.x
Barlow D, Allen L, Choate M (2016) Toward a unified treatment for emotional disorders – republished article. Behav Ther 47:838–853. https://doi.org/10.1016/j.beth.2016.11.005
Barrett L (2006a) Are emotions natural kinds? Perspect Psychol Sci 1:28–58. https://doi.org/10.1111/j.1745-6916.2006.00003.x
Barrett L (2006b) Solving the emotion paradox: categorization and the experience of emotion. Personal Soc Psychol Rev 10:20–46. https://doi.org/10.1207/s15327957pspr1001_2
Barrett L (2017) How emotions are made: the secret life of the brain. Houghton Mifflin Harcourt, New York
Barrett L, Satpute A (2013) Large-scale brain networks in affective and social neuroscience: towards an integrative functional architecture of the brain. Curr Opin Neurobiol 23:361–372. https://doi.org/10.1016/j.conb.2012.12.012
Barrett L, Lindquist K, Bliss-Moreau E, Duncan S, Gendron M, Mize J et al (2007) Of mice and men: natural kinds of emotions in the mammalian brain? A response to Panksepp and Izard. Perspect Psychol Sci 2:297–312. https://doi.org/10.1111/j.1745-6916.2007.00046.x
Barrett L, Mesquita B, Gendron M (2011) Context in emotion perception. Curr Dir Psychol Sci 20:286–290. https://doi.org/10.1177/0963721411422522
Bastos A, Usrey W, Adams R, Mangun G, Fries P, Friston K (2012) Canonical microcircuits for predictive coding. Neuron 76:695–711. https://doi.org/10.1016/j.neuron.2012.10.038
Binder J, Desai R, Graves W, Conant L (2009) Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb Cortex 19:2767–2796. https://doi.org/10.1093/cercor/bhp055
Block N (2005) Two neural correlates of consciousness. Trends Cogn Sci 9:46–52. https://doi.org/10.1016/j.tics.2004.12.006
Brosch T, Sander D (2013) The appraising brain: towards a neuro-cognitive model of appraisal processes in emotion. Emot Rev 5:163–168. https://doi.org/10.1177/1754073912468298
Brosch T, Coppin G, Scherer KR, Schwartz S, Sander D (2011) Generating value(s): psychological value hierarchies reflect context-dependent sensitivity of the reward system. Soc Neurosci 6:198–208. https://doi.org/10.1080/17470919.2010.506754
Brosch T, Coppin G, Schwartz S, Sander D (2012) The importance of actions and the worth of an object: dissociable neural systems representing core value and economic value. Soc Cogn Affect Neurosci 7:497–505. https://doi.org/10.1093/scan/nsr036
Buckner R (2013) The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron 80:807–815. https://doi.org/10.1016/j.neuron.2013.10.044
Clark A (2013) Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav Brain Sci 36:181–204. https://doi.org/10.1017/S0140525X12000477
Clark J, Watson S, Friston K (2018) What is mood? A computational perspective. Psychol Med 48(14):2277–2284. https://doi.org/10.1017/S0033291718000430
Conant C, Ashbey W (1970) Every good regulator of a system must be a model of that system. Int J Syst Sci 1:89–97. https://doi.org/10.1080/00207727008920220
Cools R, Nakamura K, Daw N (2011) Serotonin and dopamine: unifying affective, activational, and decision functions. Neuropsychopharmacology 36:98–113. https://doi.org/10.1038/npp.2010.121
Cowen P, Browning M (2015) What has serotonin to do with depression? World Psychiatry 14:158–160. https://doi.org/10.1002/wps.20229
Craig AD (2002) How do you feel? Interoception: the sense of the physiological condition of the body. Nat Rev Neurosci 3:655–666
Cunningham W, Van Bavel J, Johnsen I (2008) Affective flexibility: evaluative processing goals shape amygdala activity. Psychol Sci 19:152–160. https://doi.org/10.1111/j.1467-9280.2008.02061.x
Dayan P, Huys Q (2008) Serotonin, inhibition, and negative mood. PLoS Comput Biol 4:e4. https://doi.org/10.1371/journal.pcbi.0040004
Dehaene S (2014) Consciousness and the brain. Viking Press, New York
Dehaene S, Changeux J-P (2011) Experimental and theoretical approaches to conscious processing. Neuron 70:200–227. https://doi.org/10.1016/J.NEURON.2011.03.018
Dehaene S, Changeux J, Naccache L, Sackur J, Sergent C (2006) Conscious, preconscious, and subliminal processing: a testable taxonomy. Trends Cogn Sci 10:204–211. https://doi.org/10.1016/j.tics.2006.03.007
Dehaene S, Charles L, King J-R, Marti S (2014) Toward a computational theory of conscious processing. Curr Opin Neurobiol 25:76–84. https://doi.org/10.1016/j.conb.2013.12.005
Denton D, McKinley M, Farrell M, Egan G (2009) The role of primordial emotions in the evolutionary origin of consciousness. Conscious Cogn 18:500–514. https://doi.org/10.1016/j.concog.2008.06.009
Dolan R, Dayan P (2013) Goals and habits in the brain. Neuron 80:312–325. https://doi.org/10.1016/j.neuron.2013.09.007
Eldar E, Niv Y (2015) Interaction between emotional state and learning underlies mood instability. Nat Commun 6:6149. https://doi.org/10.1038/ncomms7149
Eldar E, Rutledge R, Dolan R, Niv Y (2016) Mood as representation of momentum. Trends Cogn Sci 20:15–24. https://doi.org/10.1016/J.TICS.2015.07.010
Eldar E, Roth C, Dayan P, Dolan R (2018) Decodability of reward learning signals predicts mood fluctuations. Curr Biol 28:1433–1439.e7. https://doi.org/10.1016/j.cub.2018.03.038
Feld G, Born J (2017) Sculpting memory during sleep: concurrent consolidation and forgetting. Curr Opin Neurobiol 44:20–27. https://doi.org/10.1016/J.CONB.2017.02.012
Feldman H, Friston K (2010) Attention, uncertainty, and free-energy. Front Hum Neurosci 4:215. https://doi.org/10.3389/fnhum.2010.00215
Felleman D, Van Essen D (1991) Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex 1:1–47
Fries P (2005) A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn Sci 9:474–480. https://doi.org/10.1016/j.tics.2005.08.011
Friston K (2005) A theory of cortical responses. Philos Trans R Soc Lond Ser B Biol Sci 360:815–836. https://doi.org/10.1098/rstb.2005.1622
Friston K (2010) The free-energy principle: a unified brain theory? Nat Rev Neurosci 11:127–138. https://doi.org/10.1038/nrn2787
Friston K, Schwartenbeck P, FitzGerald T, Moutoussis M, Behrens T, Dolan R (2014a) The anatomy of choice: dopamine and decision-making. Philos Trans R Soc Lond Ser B Biol Sci 369:20130481. https://doi.org/10.1098/rstb.2013.0481
Friston K, Stephan K, Montague R, Dolan R (2014b) Computational psychiatry: the brain as a phantastic organ. Lancet Psychiatry 1:148–158. https://doi.org/10.1016/S2215-0366(14)70275-5
Friston K, FitzGerald T, Rigoli F, Schwartenbeck P, Pezzulo G (2017a) Active inference: a process theory. Neural Comput 29:1–49. https://doi.org/10.1162/NECO_a_00912
Friston K, Lin M, Frith C, Pezzulo G, Hobson J, Ondobaka S (2017b) Active inference, curiosity and insight. Neural Comput 29:2633–2683. https://doi.org/10.1162/neco_a_00999
Friston K, Rosch R, Parr T, Price C, Bowman H (2018) Deep temporal models and active inference. Neurosci Biobehav Rev 90:486–501. https://doi.org/10.1016/J.NEUBIOREV.2018.04.004
Gazzaniga M, Ivry R, Mangun G (2014) Cognitive neuroscience: the biology of the mind, 4th edn. W. W. Norton & Company, Inc., New York
Gerlicher A, Tüscher O, Kalisch R (2018) Dopamine-dependent prefrontal reactivations explain long-term benefit of fear extinction. Nat Commun 9:4294. https://doi.org/10.1038/s41467-018-06785-y
Gläscher J, Daw N, Dayan P, O’Doherty JP (2010) States versus rewards: dissociable neural prediction error signals underlying model-based and model-free reinforcement learning. Neuron 66:585–595. https://doi.org/10.1016/j.neuron.2010.04.016
Grabenhorst F, Rolls ET, Parris BA (2008) From affective value to decision-making in the prefrontal cortex. Eur J Neurosci 28:1930–1939. https://doi.org/10.1111/j.1460-9568.2008.06489.x
Haaker J, Gaburro S, Sah A, Gartmann N, Lonsdorf T, Meier K et al (2013) Single dose of L-dopa makes extinction memories context-independent and prevents the return of fear. Proc Natl Acad Sci U S A 110:E2428–E2436. https://doi.org/10.1073/pnas.1303061110
Haidt J, Keltner D (1999) Culture and facial expression: open-ended methods find more expressions and a gradient of recognition. Cogn Emot 13:225–266. https://doi.org/10.1080/026999399379267
Harmer C, Goodwin G, Cowen P (2009) Why do antidepressants take so long to work? A cognitive neuropsychological model of antidepressant drug action. Br J Psychiatry 195:102–108. https://doi.org/10.1192/bjp.bp.108.051193
Hesp C, Smith R, Parr T, Allen M, Friston K, & Ramstead M (2019) Deeply Felt Affect: The Emergence of Valence in Deep Active Inference. https://doi.org/10.31234/osf.io/62pfd
Hietanen J, Glerean E, Hari R, Nummenmaa L (2016) Bodily maps of emotions across child development. Dev Sci 19:1111–1118. https://doi.org/10.1111/desc.12389
Hobson J, Friston K (2012) Waking and dreaming consciousness: neurobiological and functional considerations. Prog Neurobiol 98:82–98. https://doi.org/10.1016/j.pneurobio.2012.05.003
Hobson J, Hong C-H, Friston K (2014) Virtual reality and consciousness inference in dreaming. Front Psychol 5:1133. https://doi.org/10.3389/fpsyg.2014.01133
Hornak J, Bramham J, Rolls E, Morris R, O’Doherty J, Bullock P et al (2003) Changes in emotion after circumscribed surgical lesions of the orbitofrontal and cingulate cortices. Brain 126:1691–1712. https://doi.org/10.1093/brain/awg168
Huys Q, Eshel N, O’Nions E, Sheridan L, Dayan P, Roiser J (2012) Bonsai trees in your head: how the pavlovian system sculpts goal-directed choices by pruning decision trees. PLoS Comput Biol 8:e1002410. https://doi.org/10.1371/journal.pcbi.1002410
Huys Q, Guitart-Masip M, Dolan R, Dayan P (2015) Decision-theoretic psychiatry. Clin Psychol Sci 3:400–421. https://doi.org/10.1177/2167702614562040
Kalisch R, Wiech K, Critchley H, Dolan R (2006) Levels of appraisal: a medial prefrontal role in high-level appraisal of emotional material. NeuroImage 30:1458–1466. https://doi.org/10.1016/j.neuroimage.2005.11.011
Kashdan T, Barrett L, McKnight P (2015) Unpacking emotion differentiation: transforming unpleasant experience by perceiving distinctions in negativity. Curr Dir Psychol Sci 24:10–16. https://doi.org/10.1177/0963721414550708
Kennerley S, Behrens T, Wallis J (2011) Double dissociation of value computations in orbitofrontal and anterior cingulate neurons. Nat Neurosci 14:1581–1589. https://doi.org/10.1038/nn.2961
Kiebel S, Daunizeau J, Friston K (2008) A hierarchy of time-scales and the brain. PLoS Comput Biol 4:e1000209. https://doi.org/10.1371/journal.pcbi.1000209
Kihlstrom J, Mulvaney S, Tobias B, Tobis I (2000) The emotional unconscious. In: Eich E, Kihlstrom J, Bower G, Forgas J, Niedenthal P (eds) Cognition and emotion. Oxford University Press, New York, pp 30–86
Kleckner I, Zhang J, Touroutoglou A, Chanes L, Xia C, Simmons W et al (2017) Evidence for a large-scale brain system supporting allostasis and interoception in humans. Nat Hum Behav 1:0069. https://doi.org/10.1038/s41562-017-0069
Knill DCD, Pouget A (2004) The Bayesian brain: the role of uncertainty in neural coding and computation. Trends Neurosci 27:712–719. https://doi.org/10.1016/j.tins.2004.10.007
Knoch D, Pascual-Leone A, Meyer K, Treyer V, Fehr E (2006) Diminishing reciprocal fairness by disrupting the right prefrontal cortex. Science 314:829–832. https://doi.org/10.1126/science.1129156
Landry M, Lifshitz M, Raz A (2017) Brain correlates of hypnosis: a systematic review and meta-analytic exploration. Neurosci Biobehav Rev 81:75–98. https://doi.org/10.1016/J.NEUBIOREV.2017.02.020
Lane R, Weihs K, Herring A, Hishaw A, Smith R (2015) Affective agnosia: expansion of the alexithymia construct and a new opportunity to integrate and extend Freud’s legacy. Neurosci Biobehav Rev 55:594–611. https://doi.org/10.1016/j.neubiorev.2015.06.007
Lawson R, Rees G, Friston K (2014) An aberrant precision account of autism. Front Hum Neurosci 8:302. https://doi.org/10.3389/fnhum.2014.00302
Lawson R, Mathys C, Rees G (2017) Adults with autism overestimate the volatility of the sensory environment. Nat Neurosci 20:1293–1299. https://doi.org/10.1038/nn.4615
LeDoux J (2012) Rethinking the emotional brain. Neuron 73:653–676. https://doi.org/10.1016/j.neuron.2012.02.004
Lewis P, Knoblich G, Poe G (2018) How memory replay in sleep boosts creative problem-solving. Trends Cogn Sci 22:491–503. https://doi.org/10.1016/j.tics.2018.03.009
Lynn S, Laurence J-R, Kirsch I (2015) Hypnosis, suggestion, and suggestibility: an integrative model. Am J Clin Hypn 57:314–329. https://doi.org/10.1080/00029157.2014.976783
Manuello J, Vercelli U, Nani A, Costa T, Cauda F (2016) Mindfulness meditation and consciousness: an integrative neuroscientific perspective. Conscious Cogn 40:67–78. https://doi.org/10.1016/J.CONCOG.2015.12.005
Mason L, Eldar E, Rutledge R (2017) Mood instability and reward dysregulation – a neurocomputational model of bipolar disorder. JAMA Psychiat 74:1275. https://doi.org/10.1001/jamapsychiatry.2017.3163
Mather M, Clewett D, Sakaki M, Harley C (2015) Norepinephrine ignites local hot spots of neuronal excitation: how arousal amplifies selectivity in perception and memory. Behav Brain Sci 39:1–100. https://doi.org/10.1017/S0140525X15000667
Mesulam M (1998) From sensation to cognition. Brain 121:1013–1052
Mesulam M (2000) Behavioral neuroanatomy: large-scale networks, association cortex, frontal syndromes, the limbic system, and hemispheric specializations. In: Mesulam M (ed) Principles of behavioral and cognitive neurology. Oxford University Press, New York
Moors A (2013) On the causal role of appraisal in emotion. Emot Rev 5:132–140. https://doi.org/10.1177/1754073912463601
Moors A, Ellsworth PC, Scherer K, Frijda N (2013) Appraisal theories of emotion: state of the art and future development. Emot Rev 5:119–124. https://doi.org/10.1177/1754073912468165
Moran R, Campo P, Symmonds M, Stephan K, Dolan R, Friston K (2013) Free energy, precision and learning: the role of cholinergic neuromodulation. J Neurosci 33:8227–8236. https://doi.org/10.1523/JNEUROSCI.4255-12.2013
Muzur A, Pace-Schott E, Hobson J (2002) The prefrontal cortex in sleep. Trends Cogn Sci 6:475–481. https://doi.org/10.1016/S1364-6613(02)01992-7
Nielsen T (2000) A review of mentation in REM and NREM sleep: “covert” REM sleep as a possible reconciliation of two opposing models. Behav Brain Sci 23:S0140525X0000399X. https://doi.org/10.1017/S0140525X0000399X
Niv Y, Daw N, Joel D, Dayan P (2007) Tonic dopamine: opportunity costs and the control of response vigor. Psychopharmacology 191:507–520. https://doi.org/10.1007/s00213-006-0502-4
Padoa-Schioppa C, Assad J (2008) The representation of economic value in the orbitofrontal cortex is invariant for changes of menu. Nat Neurosci 11:95–102. https://doi.org/10.1038/nn2020
Panksepp J (1998) Affective neuroscience: the foundations of human and animal emotions. Oxford University Press, Oxford
Panksepp J (2005) Affective consciousness: Core emotional feelings in animals and humans. Conscious Cogn 14:30–80. https://doi.org/10.1016/j.concog.2004.10.004
Panksepp J, Biven L (2012) The archaeology of mind: neuroevolutionary origins of human emotions. W.W. Norton & Company, New York
Panksepp J, Lane R, Solms M, Smith R (2017) Reconciling cognitive and affective neuroscience perspectives on the brain basis of emotional experience. Neurosci Biobehav Rev 76(part B):187–215. https://doi.org/10.1016/j.neubiorev.2016.09.010
Parker J, Taylor G, Bagby R (2003) The 20-item Toronto alexithymia scale: III. Reliability and factorial validity in a community population. J Psychosom Res 55:269–275. https://doi.org/10.1016/S0022-3999(02)00578-0
Parr T, Friston K (2017) Working memory, attention, and salience in active inference. Sci Rep 7:14678. https://doi.org/10.1038/s41598-017-15249-0
Parr T, Friston K (2018) The anatomy of inference: generative models and brain structure. Front Comput Neurosci 12:90. https://doi.org/10.3389/fncom.2018.00090
Payne J, Kensinger E (2018) Stress, sleep, and the selective consolidation of emotional memories. Curr Opin Behav Sci 19:36–43. https://doi.org/10.1016/J.COBEHA.2017.09.006
Peck C, Salzman C (2014) The amygdala and basal forebrain as a pathway for motivationally guided attention. J Neurosci 34:13757–13767. https://doi.org/10.1523/JNEUROSCI.2106-14.2014
Peelen M, Atkinson A, Vuilleumier P (2010) Supramodal representations of perceived emotions in the human brain. J Neurosci 51:10127–10134. https://doi.org/10.1523/JNEUROSCI.2161-10.2010
Pfeiffer B, Foster D (2013) Hippocampal place-cell sequences depict future paths to remembered goals. Nature 497:74–79. https://doi.org/10.1038/nature12112
Price JL (1999) Prefrontal cortical networks related to visceral function and mood. Ann N Y Acad Sci 877:383–396
Prinz J (2006) Gut reactions: a perceptual theory of emotion. Oxford University Press, New York
Quiroga R, Reddy L, Kreiman G, Koch C, Fried I (2005) Invariant visual representation by single neurons in the human brain. Nature 435:1102–1107. https://doi.org/10.1038/nature03687
Rauss K, Born J (2017) A role of sleep in forming predictive codes. In: Cognitive neuroscience of memory consolidation. Springer, Cham, pp 117–132. https://doi.org/10.1007/978-3-319-45066-7_8
Roumis D, Frank L (2015) Hippocampal sharp-wave ripples in waking and sleeping states. Curr Opin Neurobiol 35:6–12. https://doi.org/10.1016/j.conb.2015.05.001
Russell J (1991) Culture and the categorization of emotions. Psychol Bull 110:426–450. https://doi.org/10.1037/0033-2909.110.3.426
Russell J (1994) Is there universal recognition of emotion from facial expression? A review of the cross-cultural studies. Psychol Bull 115:102–141
Saper C, Fuller P (2017) Wake-sleep circuitry: an overview. Curr Opin Neurobiol 44:186–192. https://doi.org/10.1016/j.conb.2017.03.021
Scammell T, Arrigoni E, Lipton J (2017) Neural circuitry of wakefulness and sleep. Neuron 93:747–765. https://doi.org/10.1016/j.neuron.2017.01.014
Scherer K (2009) The dynamic architecture of emotion: evidence for the component process model. Cogn Emot 23:1307–1351. https://doi.org/10.1080/02699930902928969
Schnuerch R, Kreitz C, Gibbons H, Memmert D (2016) Not quite so blind: semantic processing despite inattentional blindness. J Exp Psychol Hum Percept Perform 42:459–463. https://doi.org/10.1037/xhp0000205
Seth A (2013) Interoceptive inference, emotion, and the embodied self. Trends Cogn Sci 17:565–573. https://doi.org/10.1016/j.tics.2013.09.007
Seth A, Friston K (2016) Active interoceptive inference and the emotional brain. Philos Trans R Soc Lond B Biol Sci 371(1708):pii: 20160007
Shiota M, Kalat J (2012) Emotion, 2nd edn. Cengage Learning, Belmont
Siemer M, Mauss I, Gross J (2007) Same situation – different emotions: how appraisals shape our emotions. Emotion 7:592–600. https://doi.org/10.1037/1528-3542.7.3.592
Simons DJ, Chabris CF (1999) Gorillas in our midst: sustained inattentional blindness for dynamic events. Perception 28:1059–1074
Sizer L (2000) Towards a computational theory of mood. Br J Philos Sci 51:743–770
Smith R (2017) A neuro-cognitive defense of the unified self. Conscious Cogn 48:21–39. https://doi.org/10.1016/j.concog.2016.10.007
Smith R (2020) The three-process model of implicit and explicit emotion. In: Lane R, Nadel L (eds) Neuroscience of enduring change: implications for psychotherapy. Oxford University Press, New York, (in press)
Smith R, Lane R (2015) The neural basis of one’s own conscious and unconscious emotional states. Neurosci Biobehav Rev 57:1–29. https://doi.org/10.1016/j.neubiorev.2015.08.003
Smith R, Lane R (2016) Unconscious emotion: a cognitive neuroscientific perspective. Neurosci Biobehav Rev 69:216–238. https://doi.org/10.1016/j.neubiorev.2016.08.013
Smith R, Fass H, Lane R (2014) Role of medial prefrontal cortex in representing one’s own subjective emotional responses: a preliminary study. Conscious Cogn 29:117–130. https://doi.org/10.1016/j.concog.2014.08.002
Smith R, Braden B, Chen K, Ponce F, Lane R, Baxter L (2015) The neural basis of attaining conscious awareness of sad mood. Brain Imaging Behav 9:574–587. https://doi.org/10.1007/s11682-014-9318-8
Smith R, Alkozei A, Bao J, Smith C, Lane R, Killgore W (2017a) Resting state functional connectivity correlates of emotional awareness. NeuroImage 159:99–106. https://doi.org/10.1016/j.neuroimage.2017.07.044
Smith R, Lane R, Alkozei A, Bao J, Smith C, Sanova A et al (2017b) Maintaining the feelings of others in working memory is associated with activation of the left anterior insula and left frontal-parietal control network. Soc Cogn Affect Neurosci 12:848–860. https://doi.org/10.1093/scan/nsx011
Smith R, Thayer J, Khalsa S, Lane R (2017c) The hierarchical basis of neurovisceral integration. Neurosci Biobehav Rev 75:274–296. https://doi.org/10.1016/j.neubiorev.2017.02.003
Smith R, Killgore W, Alkozei A, Lane R (2018a) A neuro-cognitive process model of emotional intelligence. Biol Psychol 139:131–151. https://doi.org/10.1016/J.BIOPSYCHO.2018.10.012
Smith R, Killgore W, Lane R (2018b) The structure of emotional experience and its relation to trait emotional awareness: a theoretical review. Emotion 18:670–692. https://doi.org/10.1037/emo0000376
Smith R, Lane R, Alkozei A, Bao J, Smith C, Sanova A et al (2018c) The role of medial prefrontal cortex in the working memory maintenance of one’s own emotional responses. Sci Rep 8:3460. https://doi.org/10.1038/s41598-018-21896-8
Smith R, Lane R, Sanova A, Alkozei A, Smith C, Killgore WD (2018d) Common and unique neural systems underlying the working memory maintenance of emotional vs. bodily reactions to affective stimuli: the moderating role of trait emotional awareness. Front Hum Neurosci 12:370. https://doi.org/10.3389/fnhum.2018.00370
Smith R, Akozei A, Killgore W, Lane R (2018e) Nested positive feedback loops in the maintenance of major depression: an integration and extension of previous models. Brain Behav Immun 67:374–397. https://doi.org/10.1016/j.bbi.2017.09.011
Smith R, Kaszniak A, Katsanis J, Lane R, Nielsen L (2019a) The importance of identifying underlying process abnormalities in alexithymia: implications of the three-process model and a single case study illustration. Conscious Cogn 68:33–46. https://doi.org/10.1016/J.CONCOG.2018.12.004
Smith R, Lane R, Parr T, Friston K (2019b) Neurocomputational mechanisms underlying emotional awareness: insights afforded by deep active inference and their potential clinical relevance. Neurosci Biobehav Rev 107:473–491. https://doi.org/10.1016/j.neubiorev.2019.09.002
Smith R, Parr T, Friston KJ (2019c) Simulating emotions: an active inference model of emotional state inference and emotion concept learning. Front Psychol 10:2844. https://doi.org/10.3389/fpsyg.2019.02844
Smith R, Quinlan D, Schwartz GE, Sanova A, Alkozei A, Lane RD (2019d) Developmental contributions to emotional awareness. J Pers Assess 101:150–158. https://doi.org/10.1080/00223891.2017.1411917
Stickgold R, Hobson J, Fosse R, Fosse M (2001) Sleep, learning, and dreams: off-line memory reprocessing. Science 294:1052–1057. https://doi.org/10.1126/science.1063530
Terhune D, Cleeremans A, Raz A, Lynn S (2017) Hypnosis and top-down regulation of consciousness. Neurosci Biobehav Rev 81:59–74. https://doi.org/10.1016/J.NEUBIOREV.2017.02.002
Thakur E, Holmes H, Lockhart N, Carty J, Ziadni M, Doherty H et al (2017) Emotional awareness and expression training improves irritable bowel syndrome: a randomized controlled trial. Neurogastroenterol Motil 29:e13143
Tononi G, Cirelli C (2014) Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration. Neuron 81:12–34. https://doi.org/10.1016/J.NEURON.2013.12.025
Tononi G, Boly M, Massimini M, Koch C (2016) Integrated information theory: from consciousness to its physical substrate. Nat Rev Neurosci 17:450–461. https://doi.org/10.1038/nrn.2016.44
Walker M, Stickgold R (2010) Overnight alchemy: sleep-dependent memory evolution. Nat Rev Neurosci 11:218; author reply 218. https://doi.org/10.1038/nrn2762-c1
Waugh C, Lemus M, Gotlib I (2014) The role of the medial frontal cortex in the maintenance of emotional states. Soc Cogn Affect Neurosci 9:2001–2009. https://doi.org/10.1093/scan/nsu011
Widen S, Russell J (2008) Children acquire emotion categories gradually. Cogn Dev 23:291–312. https://doi.org/10.1016/j.cogdev.2008.01.002
Winkielman P, Berridge K (2004) Unconscious emotion. Curr Dir Psychol Sci 13:120–123. https://doi.org/10.1111/j.0963-7214.2004.00288.x
Wright R, Riedel R, Sechrest L, Lane R, Smith R (2017) Sex differences in emotion recognition ability: the mediating role of trait emotional awareness. Motiv Emot 42:149–160. https://doi.org/10.1007/s11031-017-9648-0
Whyte CJ, & Smith R (2020) The Predictive Global Neuronal Workspace: A Formal Active Inference Model of Visual Consciousness bioRxiv 2020.02.11.944611; https://doi.org/10.1101/2020.02.11.944611 Now published in Progress in Neurobiology https://doi.org/10.1016/j.pneurobio.2020.101918
Yeo B, Krienen F, Sepulcre J, Sabuncu M, Lashkari D, Hollinshead M et al (2011) The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol 106:1125–1165. https://doi.org/10.1152/jn.00338.2011
Zahn R, Moll J, Krueger F, Huey ED, Garrido G, Grafman J (2007) Social concepts are represented in the superior anterior temporal cortex. Proc Natl Acad Sci U S A 104:6430–6435. https://doi.org/10.1073/pnas.0607061104
Zemack-Rugar Y, Bettman J, Fitzsimons G (2007) The effects of nonconsciously priming emotion concepts on behavior. J Pers Soc Psychol 93:927–939. https://doi.org/10.1037/0022-3514.93.6.927
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Smith, R. (2021). Subjective Experience and Its Neural Basis. In: Zeise, M.L. (eds) Neuroscience for Psychologists. Springer, Cham. https://doi.org/10.1007/978-3-030-47645-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-47645-8_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-47644-1
Online ISBN: 978-3-030-47645-8
eBook Packages: Behavioral Science and PsychologyBehavioral Science and Psychology (R0)