Bibliography

    Abler, B., Walter, H., and Erk, S. (2005). Neural correlates of frustration. Neuroreport, 16(7):669–672.

    Ainslie, G. (2001). Breakdown of will. Cambridge University Press.

    Aitchison, L. and Lengyel, M. (2016). The Hamiltonian brain: efficient probabilistic inference with excitatory-inhibitory neural circuit dynamics. PLoS Computational Biology, 12(12):e1005186.

    Ambrose, R. E., Pfeiffer, B. E., and Foster, D. J. (2016). Reverse replay of hippocampal place cells is uniquely modulated by changing reward. Neuron, 91(5):1124–1136.

    Anālayo (2003). Satipaṭhna: The direct path to realization. Birmingham: Windhorse Publications.

    Andrews-Hanna, J. R. (2012). The brain’s default network and its adaptive role in internal mentation. The Neuroscientist, 18(3):251–270.

    Annas, J. E. and Barnes, J. (1985). The Modes of Scepticism: Ancient Texts and Modern Interpretations. Cambridge University Press.

    Arandjelovic, R. and Zisserman, A. (2017). Look, listen and learn. In 2017 IEEE International Conference on Computer Vision (ICCV), pages 609–617. IEEE.

    Arjovsky, M., Bottou, L., Gulrajani, I., and Lopez-Paz, D. (2019). Invariant risk minimization. arXiv preprint, arXiv:1907.02893.

    Baars, B. J. (1997). In the Theater of Consciousness: The Workspace of the Mind. Oxford University Press.

    Baars, B. J. (2002). The conscious access hypothesis: origins and recent evidence. Trends in cognitive sciences, 6(1):47–52.

    Bach, D. R. and Dayan, P. (2017). Algorithms for survival: a comparative perspective on emotions. Nature Reviews Neuroscience, 18(5):311–319.

    Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology Section A, 49(1):5–28.

    Baer, R. A. (2003). Mindfulness training as a clinical intervention: A conceptual and empirical review. Clinical psychology: Science and practice, 10(2):125–143.

    Baird, B., Smallwood, J., and Schooler, J. W. (2011). Back to the future: autobiographical planning and the functionality of mind-wandering. Consciousness and cognition, 20(4):1604–1611.

    Balcetis, E. and Dunning, D. (2006). See what you want to see: motivational influences on visual perception. Journal of personality and social psychology, 91(4):612.

    Bar, M. (2004). Visual objects in context. Nature Reviews Neuroscience, 5(8):617.

    Baumeister, R. F. (1990). Suicide as escape from self. Psychological review, 97(1):90.

    Baumeister, R. F., Bratslavsky, E., Finkenauer, C., and Vohs, K. D. (2001). Bad is stronger than good. Review of general psychology, 5(4):323.

    Baumeister, R. F., Masicampo, E., and DeWall, C. N. (2009). Prosocial benefits of feeling free: Disbelief in free will increases aggression and reduces helpfulness. Personality and social psychology bulletin, 35(2):260–268.

    Baumeister, R. F. and Vohs, K. D. (2002). The pursuit of meaningfulness in life. Handbook of positive psychology, 1:608–618.

    Baumeister, R. F., Vohs, K. D., and Tice, D. M. (2007). The strength model of self-control. Current directions in psychological science, 16(6):351–355.

    Bavelier, D., Levi, D. M., Li, R. W., Dan, Y., and Hensch, T. K. (2010). Removing brakes on adult brain plasticity: from molecular to behavioral interventions. Journal of Neuroscience, 30(45):14964–14971.

    Bechara, A. and Damasio, A. R. (2005). The somatic marker hypothesis: A neural theory of economic decision. Games and economic behavior, 52(2):336–372.

    Belk, R. W., Ger, G., and Askegaard, S. (2003). The fire of desire: A multisited inquiry into consumer passion. Journal of consumer research, 30(3):326–351.

    Bengio, Y., Ducharme, R., Vincent, P., and Jauvin, C. (2003). A neural probabilistic language model. Journal of machine learning research, 3(Feb):1137–1155.

    Beran, M. J., Perner, J., and Proust, J. (2012). Foundations of metacognition. Oxford University Press.

    Berkes, P., Orbán, G., Lengyel, M., and Fiser, J. (2011). Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment. Science, 331(6013):83–87.

    Berridge, K. C. and Kringelbach, M. L. (2015). Pleasure systems in the brain. Neuron, 86(3):646–664.

    Beyens, I., Pouwels, J. L., van Driel, I. I., Keijsers, L., and Valkenburg, P. M. (2020). The effect of social media on well-being differs from adolescent to adolescent. Scientific Reports, 10(1):1–11.

    Bhatnagar, S., Precup, D., Silver, D., Sutton, R. S., Maei, H. R., and Szepesvári, C. (2009). Convergent temporal-difference learning with arbitrary smooth function approximation. In Advances in Neural Information Processing Systems, pages 1204–1212.

    Birch, J. (2016). Natural selection and the maximization of fitness. Biological Reviews, 91(3):712–727.

    Birch, J. (2017). Animal sentience and the precautionary principle. Animal Sentience: An Interdisciplinary Journal on Animal Feeling, 2(16):1.

    Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J., Segal, Z. V., Abbey, S., Speca, M., Velting, D., et al. (2004). Mindfulness: a proposed operational definition. Clinical psychology: Science and practice, 11(3):230.

    Block, N. (1995). On a confusion about a function of consciousness. Behavioral and brain sciences, 18(2):227–247.

    Borji, A., Cheng, M.-M., Jiang, H., and Li, J. (2015). Salient object detection: A benchmark. IEEE transactions on image processing, 24(12):5706–5722.

    Bostrom, N. (2003). Are we living in a computer simulation? The Philosophical Quarterly, 53(211):243–255.

    Bottou, L. (2003). Stochastic learning. In Summer School on Machine Learning, pages 146–168. Springer.

    Botvinick, M. M. (2012). Hierarchical reinforcement learning and decision making. Current opinion in neurobiology, 22(6):956–962.

    Botvinick, M. M. and Cohen, J. D. (2014). The computational and neural basis of cognitive control: charted territory and new frontiers. Cognitive science, 38(6):1249–1285.

    Bowie, E. (2016). Gymnosophists. In Oxford Classical Dictionary. Oxford University Press.

    Brach, T. (2004). Radical acceptance. Bantam.

    Brahm, A. (2006). Mindfulness, Bliss, and Beyond. Somerville: Wisdom Publications.

    Bratman, M. (1987). Intention, plans, and practical reason. CSLI Publications.

    Brewer, J. A., Elwafi, H. M., and Davis, J. H. (2014). Craving to quit: Psychological models and neurobiological mechanisms of mindfulness training as treatment for addictions. Psychol. Addict. Behav., 27(2):366–79.

    Brewer, J. A., Worhunsky, P. D., Gray, J. R., Tang, Y.-Y., Weber, J., and Kober, H. (2011). Meditation experience is associated with differences in default mode network activity and connectivity. Proceedings of the National Academy of Sciences, 108(50):20254–20259.

    Brincat, S. L. and Connor, C. E. (2004). Underlying principles of visual shape selectivity in posterior inferotemporal cortex. Nature neuroscience, 7(8):880.

    Brochu, E., Cora, V. M., and De Freitas, N. (2010). A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. arXiv preprint, arXiv:1012.2599.

    Brodaric, B. and Neuhaus, F. (2020). Foundations for an ontology of belief, desire and intention. In Formal Ontology in Information Systems: Proceedings of the 11th International Conference (FOIS 2020), volume 330, page 140. IOS Press.

    Brodersen, K. H., Deserno, L., Schlagenhauf, F., Lin, Z., Penny, W. D., Buhmann, J. M., and Stephan, K. E. (2014). Dissecting psychiatric spectrum disorders by generative embedding. NeuroImage: Clinical, 4:98–111.

    Brooks, R. A. (1991). Intelligence without representation. Artificial intelligence, 47(1-3):139–159.

    Brooks, R. A. (1999). Cambrian intelligence: The early history of the new AI. MIT press.

    Brown, N. and Sandholm, T. (2018). Superhuman AI for heads-up no-limit poker: Libratus beats top professionals. Science, 359(6374):418–424.

    Browne, C. B., Powley, E., Whitehouse, D., Lucas, S. M., Cowling, P. I., Rohlfshagen, P., Tavener, S., Perez, D., Samothrakis, S., and Colton, S. (2012). A survey of Monte Carlo tree search methods. IEEE Transactions on Computational Intelligence and AI in games, 4(1):1–43.

    Bruno, M.-A., Vanhaudenhuyse, A., Thibaut, A., Moonen, G., and Laureys, S. (2011). From unresponsive wakefulness to minimally conscious plus and functional locked-in syndromes: recent advances in our understanding of disorders of consciousness. Journal of neurology, 258(7):1373–1384.

    Buckner, R. L. (2010). The role of the hippocampus in prediction and imagination. Annual review of psychology, 61:27–48.

    Buckner, R. L., Andrews-Hanna, J. R., and Schacter, D. L. (2008). The brain’s default network. Annals of the New York Academy of Sciences, 1124(1):1–38.

    Bueno-Gómez, N. (2017). Conceptualizing suffering and pain. Philosophy, Ethics, and Humanities in Medicine, 12(1):7.

    Bullmore, E. and Sporns, O. (2012). The economy of brain network organization. Nature Reviews Neuroscience, 13(5):336.

    Burke, B. L., Martens, A., and Faucher, E. H. (2010). Two decades of terror management theory: A meta-analysis of mortality salience research. Personality and Social Psychology Review, 14(2):155–195.

    Butti, C., Santos, M., Uppal, N., and Hof, P. R. (2013). Von Economo neurons: clinical and evolutionary perspectives. Cortex, 49(1):312–326.

    Buzsáki, G. (1996). The hippocampo-neocortical dialogue. Cerebral Cortex, 6(2):81–92.

    Campbell, M., Hoane Jr, A. J., and Hsu, F.-h. (2002). Deep blue. Artificial intelligence, 134(1-2):57–83.

    Carmody, J. (2015). Reconceptualizing mindfulness. Handbook of mindfulness: Theory, research, and practice, pages 62–78.

    Carruthers, P. (2009). How we know our own minds: The relationship between mindreading and metacognition. Behavioral and brain sciences, 32(2):121–138.

    Carver, C. (2003). Pleasure as a sign you can attend to something else: Placing positive feelings within a general model of affect. Cognition & Emotion, 17(2):241–261.

    Cassell, E. (2002). Compassion. In Snyder, C. and Lopez, S., editors, The Oxford handbook of positive psychology. Oxford University Press.

    Cassell, E. J. (1982). The nature of suffering and the goals of medicine. N Engl J Med, 306:639–645.

    Cassell, E. J. (1989). The relationship between pain and suffering. In Hill, C. S. J. and Fields, W. S., editors, Advances in Pain Research and Therapy. Raven Press: New York.

    Castrén, E. and Antila, H. (2017). Neuronal plasticity and neurotrophic factors in drug responses. Molecular psychiatry, 22(8):1085.

    Chah, A. (2001). Being Dharma: The essence of the Buddha’s teachings. Shambhala Publications.

    Chalmers, D. J. (1995). Facing up to the problem of consciousness. Journal of consciousness studies, 2(3):200–219.

    Chalmers, D. J. (1996). The conscious mind: In search of a fundamental theory. Oxford university press.

    Chan, A. (2018). Laozi. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Chapman, H. A. and Anderson, A. K. (2012). Understanding disgust. Annals of the New York Academy of Sciences, 1251(1):62–76.

    Chaslot, G. M.-B., Winands, M. H., and van Den Herik, H. J. (2008). Parallel Monte Carlo tree search. In International Conference on Computers and Games, pages 60–71. Springer.

    Chella, A. and Manzotti, R. (2007). Artificial consciousness. Andrews UK Limited.

    Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., and Yuille, A. L. (2018). DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE transactions on pattern analysis and machine intelligence, 40(4):834–848.

    Chin, J. and Schooler, J. W. (2010). Meta-awareness. Encyclopedia of consciousness, 2:33–41.

    Choudhury, S. and Blakemore, S.-J. (2006). Intentions, actions, and the self. In Pockett, S., Banks, W. P., and Gallagher, S., editors, Does consciousness cause behavior, pages 39–51. Boston: MIT Press.

    Christoff, K., Gordon, A. M., Smallwood, J., Smith, R., and Schooler, J. W. (2009). Experience sampling during fMRI reveals default network and executive system contributions to mind wandering. Proceedings of the National Academy of Sciences, 106(21):8719–8724.

    Clark, A. (2013). Whatever next? predictive brains, situated agents, and the future of cognitive science. Behavioral and brain sciences, 36(3):181–204.

    Cleeremans, A. and Tallon-Baudry, C. (2021). The function of consciousness is to generate experience. PsyArXiv.

    Cohen, M., Quintner, J., and van Rysewyk, S. (2018). Reconsidering the International Association for the Study of Pain definition of pain. Pain Reports, 3(2):e634.

    Cohen, P. R. and Levesque, H. J. (1990). Intention is choice with commitment. Artificial intelligence, 42(2-3):213–261.

    Colombetti, G. (2005). Appraising valence. Journal of consciousness studies, 12(8-9):103–126.

    Colton, S., de Mántaras, R. L., and Stock, O. (2009). Computational creativity: Coming of age. AI Magazine, 30(3):11.

    Corballis, M. C. (2019). Language, memory, and mental time travel: An evolutionary perspective. Frontiers in human neuroscience, 13:217.

    Corns, J. (2016). Pain eliminativism: scientific and traditional. Synthese, 193(9):2949–2971.

    Costa, V. D. and Averbeck, B. B. (2020). Primate orbitofrontal cortex codes information relevant for managing explore–exploit tradeoffs. Journal of Neuroscience, 40(12):2553–2561.

    Craig, A. D. (2003). A new view of pain as a homeostatic emotion. Trends in neurosciences, 26(6):303–307.

    Craig, A. D. (2009). How do you feel–now? the anterior insula and human awareness. Nature reviews neuroscience, 10(1):59–70.

    Crick, F. and Koch, C. (2003). A framework for consciousness. Nature neuroscience, 6(2):119.

    Crisp, R. (2017). Well-being. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Cristia, A., Dupoux, E., Gurven, M., and Stieglitz, J. (2019). Child-directed speech is infrequent in a forager-farmer population: A time allocation study. Child development, 90(3):759–773.

    Critchley, H. and Seth, A. (2012). Will studies of macaque insula reveal the neural mechanisms of self-awareness? Neuron, 74(3):423–426.

    Csikszentmihalyi, M. (1997). Finding flow: The psychology of engagement with everyday life. Basic Books.

    Dahl, C. J., Lutz, A., and Davidson, R. J. (2015). Reconstructing and deconstructing the self: cognitive mechanisms in meditation practice. Trends in cognitive sciences, 19(9):515–523.

    Dalai Lama, Lhündrub, K. P., and Cabezón, J. I. (2011). Meditation on the Nature of Mind. Boston: Wisdom Publications.

    Damasio, A. (1994). Descartes’ error: Emotion, Reason, and the Human Brain. Putnam Publishing.

    Damoiseaux, J., Rombouts, S., Barkhof, F., Scheltens, P., Stam, C., Smith, S. M., and Beckmann, C. (2006). Consistent resting-state networks across healthy subjects. Proceedings of the national academy of sciences, 103(37):13848–13853.

    Dasgupta, P. and Maskin, E. (2005). Uncertainty and hyperbolic discounting. American Economic Review, 95(4):1290–1299.

    Davidson, J., Liebald, B., Liu, J., Nandy, P., Van Vleet, T., Gargi, U., Gupta, S., He, Y., Lambert, M., Livingston, B., et al. (2010). The YouTube video recommendation system. In Proceedings of the fourth ACM conference on Recommender systems, pages 293–296. ACM.

    d’Avila Garcez, A. S., Broda, K. B., and Gabbay, D. M. (2012). Neural-symbolic learning systems: foundations and applications. Springer Science & Business Media.

    Daw, N. D., Niv, Y., and Dayan, P. (2005). Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nature neuroscience, 8(12):1704–1711.

    Dawkins, R. (1986). The blind watchmaker: Why the evidence of evolution reveals a universe without design. WW Norton & Company.

    De Berker, A. O., Rutledge, R. B., Mathys, C., Marshall, L., Cross, G. F., Dolan, R. J., and Bestmann, S. (2016). Computations of uncertainty mediate acute stress responses in humans. Nature Communications, 7:10996.

    De Brigard, F. and Prinz, J. (2010). Attention and consciousness. Wiley Interdisciplinary Reviews: Cognitive Science, 1(1):51–59.

    de Catanzaro, D. (1991). Evolutionary limits to self-preservation. Ethology and Sociobiology, 12(1):13–28.

    Degrazia, D. (1998). Suffering. In Routledge Encyclopedia of Philosophy. Taylor and Francis.

    Dehaene, S. and Naccache, L. (2001). Towards a cognitive neuroscience of consciousness: basic evidence and a workspace framework. Cognition, 79(1-2):1–37.

    Dennett, D. C. (1992). The self as the center of narrative gravity. In Kessel, F., Cole, P., and Johnson, D., editors, Self and consciousness: Multiple Perspectives. Hillsdale, NJ: Erlbaum.

    Dhawale, A. K., Smith, M. A., and Ölveczky, B. P. (2017). The role of variability in motor learning. Annual review of neuroscience, 40:479–498.

    Diamond, A. (2013). Executive functions. Annual review of psychology, 64:135–168.

    Diba, K. and Buzsáki, G. (2007). Forward and reverse hippocampal place-cell sequences during ripples. Nature neuroscience, 10(10):1241.

    Dietterich, T. G. (2000). Hierarchical reinforcement learning with the MAXQ value function decomposition. Journal of Artificial Intelligence Research, 13:227–303.

    Dignum, F., Morley, D., Sonenberg, E. A., and Cavedon, L. (2000). Towards socially sophisticated bdi agents. In Proceedings fourth international conference on multiagent systems, pages 111–118. IEEE.

    Diuk, C., Cohen, A., and Littman, M. L. (2008). An object-oriented representation for efficient reinforcement learning. In Proceedings of the 25th international conference on machine learning (ICML), pages 240–247.

    Dolan, R. J. and Dayan, P. (2013). Goals and habits in the brain. Neuron, 80(2):312–325.

    Doya, K. and Uchibe, E. (2005). The cyber rodent project: Exploration of adaptive mechanisms for self-preservation and self-reproduction. Adaptive Behavior, 13(2):149–160.

    Doyon, J., Penhune, V., and Ungerleider, L. G. (2003). Distinct contribution of the cortico-striatal and cortico-cerebellar systems to motor skill learning. Neuropsychologia, 41(3):252–262.

    Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., et al. (2017). Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature medicine, 23(1):28.

    Duffy, K. R. and Mitchell, D. E. (2013). Darkness alters maturation of visual cortex and promotes fast recovery from monocular deprivation. Current biology, 23(5):382–386.

    Dunne, J. D., Thompson, E., and Schooler, J. (2019). Mindful meta-awareness: Sustained and non-propositional. Current Opinion in Psychology, 28:307–311.

    Edwards, S. D. (2003). Three concepts of suffering. Medicine, Health Care and Philosophy, 6(1):59–66.

    Eickenberg, M., Gramfort, A., Varoquaux, G., and Thirion, B. (2017). Seeing it all: Convolutional network layers map the function of the human visual system. NeuroImage, 152:184–194.

    Eisenberger, N. I. and Lieberman, M. D. (2004). Why rejection hurts: a common neural alarm system for physical and social pain. Trends in cognitive sciences, 8(7):294–300.

    Eisenreich, B. R., Akaishi, R., and Hayden, B. Y. (2017). Control without controllers: toward a distributed neuroscience of executive control. Journal of cognitive neuroscience, 29(10):1684–1698.

    Emmons, R. and Shelton, C. (2002). Gratitude and the science of positive psychology. In Snyder, C. and Lopez, S., editors, The Oxford handbook of positive psychology. Oxford University Press.

    Evans, J. S. B. (2008). Dual-processing accounts of reasoning, judgment, and social cognition. Annu. Rev. Psychol., 59:255–278.

    Federman, A. (2010). What kind of free will did the Buddha teach? Philosophy East and West, pages 1–19.

    Feinman, R. and Lake, B. M. (2018). Learning inductive biases with simple neural networks. arXiv preprint, arXiv:1802.02745.

    Feldman, G., Greeson, J., and Senville, J. (2010). Differential effects of mindful breathing, progressive muscle relaxation, and loving-kindness meditation on decentering and negative reactions to repetitive thoughts. Behaviour research and therapy, 48(10):1002–1011.

    Fink, G. (2017). Stress: Concepts, definition and history. In Reference Module in Neuroscience and Biobehavioral Psychology, pages 1–9. Elsevier.

    Firestone, C. and Scholl, B. J. (2014). ”Top-down” effects where none should be found: The El Greco fallacy in perception research. Psychological science, 25(1):38–46.

    Fleming, S. M., Dolan, R. J., and Frith, C. D. (2012). Metacognition: computation, biology and function.

    Fletcher, G., editor (2015). The Routledge handbook of philosophy of well-being. Routledge.

    Fox, K. C. and Beaty, R. E. (2019). Mind-wandering as creative thinking: neural, psychological, and theoretical considerations. Current Opinion in Behavioral Sciences, 27:123–130.

    Fox, K. C., Nijeboer, S., Solomonova, E., Domhoff, G. W., and Christoff, K. (2013). Dreaming as mind wandering: evidence from functional neuroimaging and first-person content reports. Frontiers in human neuroscience, 7.

    Fox, M. D. and Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature reviews neuroscience, 8(9):700.

    Frady, E. P., Kent, S. J., Olshausen, B. A., and Sommer, F. T. (2020). Resonator networks, 1: An efficient solution for factoring high-dimensional, distributed representations of data structures. Neural computation, 32(12):2311–2331.

    Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American psychologist, 56(3):218.

    Freeman, J. B. and Johnson, K. L. (2016). More than meets the eye: Split-second social perception. Trends in cognitive sciences, 20(5):362–374.

    Fresco, D. M., Moore, M. T., van Dulmen, M. H., Segal, Z. V., Ma, S. H., Teasdale, J. D., and Williams, J. M. G. (2007). Initial psychometric properties of the experiences questionnaire: validation of a self-report measure of decentering. Behavior therapy, 38(3):234–246.

    Friese, M., Messner, C., and Schaffner, Y. (2012). Mindfulness meditation counteracts self-control depletion. Consciousness and cognition, 21(2):1016–1022.

    Frijda, N. H. (2016). The evolutionary emergence of what we call ”emotions”. Cognition and Emotion, 30(4):609–620.

    Friston, K. (2010). The free-energy principle: a unified brain theory? Nature reviews neuroscience, 11(2):127.

    Frith, C. (2002). Attention to action and awareness of other minds. Consciousness and cognition, 11(4):481–487.

    Frith, C. (2010). What is consciousness for? Pragmatics & Cognition, 18(3):497–551.

    Frith, C. (2012). Explaining delusions of control: The comparator model 20 years on. Consciousness and cognition, 21(1):52–54.

    Gallagher, S. (2000). Philosophical conceptions of the self: implications for cognitive science. Trends in cognitive sciences, 4(1):14–21.

    Gallagher, S. (2003). Phenomenology and experimental design toward a phenomenologically enlightened experimental science. Journal of consciousness studies, 10(9-10):85–99.

    Gallagher, S. and Shear, J., editors (1999). Models of the Self. Imprint Academic.

    Gao, T., Zhou, Y., Li, W., Pfabigan, D. M., and Han, S. (2020). Neural mechanisms of reinforcement learning under mortality threat. Social neuroscience, 15(2):170–185.

    Gärdenfors, P. (2004). Conceptual spaces: The geometry of thought. MIT press.

    Garfield, J. L. (1990). Epoche and śunyatā: Skepticism east and west. Philosophy East and West, pages 285–307.

    Garfield, J. L. (2010). What is it like to be a bodhisattva? moral phenomenology in śāntidevas bodhicaryāvatāra. Journal of the International Association of Buddhist Studies, pages 333–357.

    Garland, E., Froeliger, B., and Howard, M. (2014). Mindfulness training targets neurocognitive mechanisms of addiction at the attention-appraisal-emotion interface. Frontiers in psychiatry, 4:173.

    Georgievski, I. and Aiello, M. (2015). HTN planning: Overview, comparison, and beyond. Artificial Intelligence, 222:124–156.

    Gershman, S. J. (2017). Reinforcement learning and causal models. The Oxford handbook of causal reasoning, page 295.

    Gershman, S. J., Horvitz, E. J., and Tenenbaum, J. B. (2015). Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. Science, 349(6245):273–278.

    Gerstner, W., Lehmann, M., Liakoni, V., Corneil, D., and Brea, J. (2018). Eligibility traces and plasticity on behavioral time scales: experimental support of neohebbian three-factor learning rules. Frontiers in neural circuits, 12.

    Gigerenzer, G. and Gaissmaier, W. (2011). Heuristic decision making. Annual review of psychology, 62:451–482.

    Goertzel, B. (2012). Perception processing for general intelligence: Bridging the symbolic/subsymbolic gap. In International Conference on Artificial General Intelligence, pages 79–88. Springer.

    Goodman, B. and Flaxman, S. (2017). European union regulations on algorithmic decision-making and a ”right to explanation”. AI magazine, 38(3):50–57.

    Gopnik, A. (2009). Could David Hume have known about Buddhism?: Charles François Dolu, the Royal College of La Flčche, and the global Jesuit intellectual network. Hume Studies, 35(1/2):5–28.

    Gorder, P. F. (2007). Multicore processors for science and engineering. Computing in science & engineering, 9(2):3–7.

    Grabovac, A. D., Lau, M. A., and Willett, B. R. (2011). Mechanisms of mindfulness: A Buddhist psychological model. Mindfulness, 2(3):154–166.

    Grafen, A. (2008). The simplest formal argument for fitness optimization. Journal of genetics, 87(4):421–433.

    Graser, J. and Stangier, U. (2018). Compassion and loving-kindness meditation: an overview and prospects for the application in clinical samples. Harvard Review of Psychiatry, 26(4):201–215.

    Graves, A., Wayne, G., Reynolds, M., Harley, T., Danihelka, I., Grabska-Barwińska, A., Colmenarejo, S. G., Grefenstette, E., Ramalho, T., Agapiou, J., et al. (2016). Hybrid computing using a neural network with dynamic external memory. Nature, 538(7626):471.

    Green, D. M. and Swets, J. A. (1988). Signal detection theory and psychophysics. Wiley: New York.

    Greff, K., Rasmus, A., Berglund, M., Hao, T., Valpola, H., and Schmidhuber, J. (2016). Tagger: Deep unsupervised perceptual grouping. In Advances in Neural Information Processing Systems, pages 4484–4492.

    Gross, C. T. and Canteras, N. S. (2012). The many paths to fear. Nature Reviews Neuroscience, 13(9):651.

    Gruber, M. J., Ritchey, M., Wang, S.-F., Doss, M. K., and Ranganath, C. (2016). Post-learning hippocampal dynamics promote preferential retention of rewarding events. Neuron, 89(5):1110–1120.

    Güçlü, U. and van Gerven, M. A. (2015). Deep neural networks reveal a gradient in the complexity of neural representations across the ventral stream. Journal of Neuroscience, 35(27):10005–10014.

    Guestrin, C., Koller, D., Gearhart, C., and Kanodia, N. (2003). Generalizing plans to new environments in relational MDPs. In Proceedings of the 18th international joint conference on Artificial intelligence, pages 1003–1010. Morgan Kaufmann Publishers Inc.

    Guidotti, R., Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., and Pedreschi, D. (2018). A survey of methods for explaining black box models. ACM Computing Surveys (CSUR), 51(5):93.

    Gunaratana, B. H. (2010). Mindfulness in plain English. ReadHowYouWant.com.

    Gutmann, M. U., Corander, J., et al. (2016). Bayesian optimization for likelihood-free inference of simulator-based statistical models. Journal of Machine Learning Research, 17:1–47.

    Gutmann, M. U., Dutta, R., Kaski, S., and Corander, J. (2018). Likelihood-free inference via classification. Statistics and Computing, 28(2):411–425.

    Gutmann, M. U. and Hyvärinen, A. (2012). Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics. J. of Machine Learning Research, 13:307–361.

    Guyer, P. and Horstmann, R.-P. (2018). Idealism. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Hadany, L., Beker, T., Eshel, I., and Feldman, M. W. (2006). Why is stress so deadly? An evolutionary perspective. Proceedings of the Royal Society of London B: Biological Sciences, 273(1588):881–885.

    Hadot, P. (2002). Exercices spirituels et philosophie antique. Albin Michel, revised and augmented edition. Earlier edition partly translated as Philosophy as a Way of Life, Wiley, 1995.

    Haggard, P. and Chambon, V. (2012). Sense of agency. Current Biology, 22(10):R390–R392.

    Haidt, J. (2003). The moral emotions. In Davidson, R. J., Scherer, K. R., and Goldsmith, H. H., editors, Handbook of affective sciences, pages 852–870. Oxford: Oxford University Press.

    Han, C., O’Tuathaigh, C. M., van Trigt, L., Quinn, J. J., Fanselow, M. S., Mongeau, R., Koch, C., and Anderson, D. J. (2003). Trace but not delay fear conditioning requires attention and the anterior cingulate cortex. Proceedings of the National Academy of Sciences, 100(22):13087–13092.

    Hardt, M., Recht, B., and Singer, Y. (2016). Train faster, generalize better: Stability of stochastic gradient descent. In International Conference on Machine Learning, pages 1225–1234. PMLR.

    Hari, R. (2017). From brain–environment connections to temporal dynamics and social interaction: principles of human brain function. Neuron, 94(5):1033–1039.

    Hari, R., Henriksson, L., Malinen, S., and Parkkonen, L. (2015). Centrality of social interaction in human brain function. Neuron, 88(1):181–193.

    Hari, R., Parkkonen, L., and Nangini, C. (2010). The brain in time: insights from neuromagnetic recordings. Annals of the New York Academy of Sciences, 1191(1):89–109.

    Harnad, S. (1990). The symbol grounding problem. Physica D: Nonlinear Phenomena, 42(1-3):335–346.

    Harnad, S. (2017). To cognize is to categorize: Cognition is categorization. In Handbook of Categorization in Cognitive Science (Second Edition), pages 21–54. Elsevier.

    Harvey, P. (1995). The selfless mind: Personality, consciousness and nirvana in early Buddhism. Routledge.

    Harvey, P. (2009). Theravada philosophy of mind and the person. Buddhist philosophy: Essential readings, pages 265–74.

    Hassabis, D., Kumaran, D., Vann, S. D., and Maguire, E. A. (2007). Patients with hippocampal amnesia cannot imagine new experiences. Proceedings of the National Academy of Sciences, 104(5):1726–1731.

    Hayes, S. C. and Pierson, H. (2005). Acceptance and commitment therapy. In Freeman, A., editor, Encyclopedia of Cognitive Behavior Therapy. Springer.

    Hazan, E., Kakade, S., Singh, K., and Van Soest, A. (2019). Provably efficient maximum entropy exploration. In International Conference on Machine Learning, pages 2681–2691. PMLR.

    He, H.-Y., Hodos, W., and Quinlan, E. M. (2006). Visual deprivation reactivates rapid ocular dominance plasticity in adult visual cortex. Journal of Neuroscience, 26(11):2951–2955.

    Heatherton, T. F. (2011). Neuroscience of self and self-regulation. Annual review of psychology, 62:363–390.

    Heatherton, T. F., Wyland, C. L., and Lopez, S. (2003). Assessing self-esteem. Positive psychological assessment: A handbook of models and measures, pages 219–233.

    Heathwood, C. (2015). Desire-fulfillment theory. In Fletcher, G., editor, The Routledge handbook of philosophy of well-being. Routledge.

    Hebb, D. O. (1949). The organization of behavior; a neuropsycholocigal theory. A Wiley Book in Clinical Psychology., pages 62–78.

    Herman, A. (1979). A solution to the paradox of desire in buddhism. Philosophy East and West, 29(1):91–94.

    Hesslow, G. (2002). Conscious thought as simulation of behaviour and perception. Trends in cognitive sciences, 6(6):242–247.

    Hirsh, J. B., Mar, R. A., and Peterson, J. B. (2012). Psychological entropy: a framework for understanding uncertainty-related anxiety. Psychological review, 119(2):304.

    Hirshleifer, J. (1987). On the emotions as guarantors of threats and promises. In The latest on the best: Essays on evolution and optimality, pages 307–326. MIT Press: Cambridge, MA.

    Hobfoll, S. E. (1989). Conservation of resources: a new attempt at conceptualizing stress. American psychologist, 44(3):513.

    Hochreiter, S. and Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8):1735–1780.

    Hoffmaster, B. (2014). Understanding suffering. In R. Green, N. P., editor, Suffering and Bioethics, pages 3–53. Oxford University Press.

    Hofmann, S. G., Grossman, P., and Hinton, D. E. (2011). Loving-kindness and compassion meditation: Potential for psychological interventions. Clinical psychology review, 31(7):1126–1132.

    Hofmann, W., Friese, M., and Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on psychological science, 4(2):162–176.

    Holroyd, C. B. and Coles, M. G. (2002). The neural basis of human error processing: reinforcement learning, dopamine, and the error-related negativity. Psychological review, 109(4):679.

    Hölzel, B. K., Lazar, S. W., Gard, T., Schuman-Olivier, Z., Vago, D. R., and Ott, U. (2011). How does mindfulness meditation work? proposing mechanisms of action from a conceptual and neural perspective. Perspectives on psychological science, 6(6):537–559.

    Hommel, B. (2013). Dancing in the dark: No role for consciousness in action control. Frontiers in Psychology, 4:380.

    Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the national academy of sciences, 79(8):2554–2558.

    Hoyer, P. O. and Hyvärinen, A. (2003). Interpreting neural response variability as Monte Carlo sampling of the posterior. In Advances in neural information processing systems, pages 293–300.

    Hüllermeier, E. and Waegeman, W. (2021). Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods. Machine Learning, 110(3):457–506.

    Hume, D. (1739). A Treatise of Human Nature. Reprinted by Project Gutenberg.

    Huys, Q. J. and Dayan, P. (2009). A Bayesian formulation of behavioral control. Cognition, 113(3):314–328.

    Hyvärinen, A., Hoyer, P. O., and Hurri, J. (2009). Natural Image Statistics: A probabilistic approach to early computational vision. Springer.

    Hyvärinen, A., Karhunen, J., and Oja, E. (2001). Independent Component Analysis. Wiley Interscience.

    Hyvärinen, A. and Morioka, H. (2016). Unsupervised feature extraction by time-contrastive learning and nonlinear ICA. In Advances in Neural Information Processing Systems (NIPS2016).

    Hyvärinen, A. and Morioka, H. (2017). Nonlinear ICA of temporally dependent stationary sources. In Proc. Artificial Intelligence and Statistics (AISTATS2017), Fort Lauderdale, Florida.

    Hyvärinen, A. and Oja, E. (1998). Independent component analysis by general nonlinear hebbian-like learning rules. signal processing, 64(3):301–313.

    Iacoboni, M. (2005). Neural mechanisms of imitation. Current opinion in neurobiology, 15(6):632–637.

    Iannetti, G. D. and Mouraux, A. (2010). From the neuromatrix to the pain matrix (and back). Experimental brain research, 205(1):1–12.

    Iannetti, G. D., Salomons, T. V., Moayedi, M., Mouraux, A., and Davis, K. D. (2013). Beyond metaphor: contrasting mechanisms of social and physical pain. Trends in cognitive sciences, 17(8):371–378.

    Insel, T. R. and Cuthbert, B. N. (2015). Brain disorders? Precisely. Science, 348(6234):499–500.

    Inzlicht, M., Shenhav, A., and Olivola, C. Y. (2018). The effort paradox: Effort is both costly and valued. Trends in cognitive sciences, 22(4):337–349.

    Jacob, J., Kent, M., Benson-Amram, S., Herculano-Houzel, S., Raghanti, M. A., Ploppert, E., Drake, J., Hindi, B., Natale, N. R., Daniels, S., et al. (2021). Cytoarchitectural characteristics associated with cognitive flexibility in raccoons. Journal of Comparative Neurology.

    Janet, P. (1889). L’Automatisme psychologique. Paris: Felix Alcan.

    Kabat-Zinn, J. (2012). Mindfulness for beginners: Reclaiming the present momentand your life. Sounds True.

    Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux: New York.

    Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., et al. (2019). Advances and open problems in federated learning. arXiv preprint, arXiv:1912.04977.

    Kane, M. J., Brown, L. H., McVay, J. C., Silvia, P. J., Myin-Germeys, I., and Kwapil, T. R. (2007). For whom the mind wanders, and when: An experience-sampling study of working memory and executive control in daily life. Psychological science, 18(7):614–621.

    Karlsson, M. P. and Frank, L. M. (2009). Awake replay of remote experiences in the hippocampus. Nature Neuroscience, 12(7):913–918.

    Kasser, T. and Sheldon, K. M. (2000). Of wealth and death: Materialism, mortality salience, and consumption behavior. Psychological science, 11(4):348–351.

    Kavanagh, D. J., Andrade, J., and May, J. (2005). Imaginary relish and exquisite torture: the elaborated intrusion theory of desire. Psychological review, 112(2):446.

    Keramati, M. and Gutkin, B. (2014). Homeostatic reinforcement learning for integrating reward collection and physiological stability. Elife, 3:e04811.

    Kersten, D., Mamassian, P., and Yuille, A. (2004). Object perception as Bayesian inference. Annual Review of Psychology, 55:271–304.

    Khemakhem, I., Kingma, D. P., Monti, R. P., and Hyvärinen, A. (2020). Variational autoencoders and nonlinear ICA: A unifying framework. In Proc. Artificial Intelligence and Statistics (AISTATS2020).

    Killingsworth, M. A. and Gilbert, D. T. (2010). A wandering mind is an unhappy mind. Science, 330(6006):932–932.

    Kirchner, H. and Thorpe, S. J. (2006). Ultra-rapid object detection with saccadic eye movements: Visual processing speed revisited. Vision research, 46(11):1762–1776.

    Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al. (2017). Overcoming catastrophic forgetting in neural networks. Proceedings of the national academy of sciences, 114(13):3521–3526.

    Kiviniemi, V., Kantola, J.-H., Jauhiainen, J., Hyvärinen, A., and Tervonen, O. (2003). Independent component analysis of nondeterministic fMRI signal sources. Neuroimage, 19(2):253–260.

    Klein, C. (2007). An imperative theory of pain. The Journal of Philosophy, 104(10):517–532.

    Klinger, E. (2013). Goal commitments and the content of thoughts and dreams: Basic principles. Frontiers in Psychology, 4:415.

    Koechlin, E. and Summerfield, C. (2007). An information theoretical approach to prefrontal executive function. Trends in cognitive sciences, 11(6):229–235.

    Konstan, D. (2018). Epicurus. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Koolhaas, J., Bartolomucci, A., Buwalda, B. d., De Boer, S., Flügge, G., Korte, S., Meerlo, P., Murison, R., Olivier, B., Palanza, P., et al. (2011). Stress revisited: a critical evaluation of the stress concept. Neuroscience & Biobehavioral Reviews, 35(5):1291–1301.

    Kording, K. P., Tenenbaum, J. B., and Shadmehr, R. (2007). The dynamics of memory as a consequence of optimal adaptation to a changing body. Nature neuroscience, 10(6):779.

    Korenberg, A. T. and Ghahramani, Z. (2002). A Bayesian view of motor adaptation. Current Psychology of Cognition, 21(4/5):537–564.

    Kőszegi, B. and Rabin, M. (2006). A model of reference-dependent preferences. The Quarterly Journal of Economics, 121(4):1133–1165.

    Kouider, S., De Gardelle, V., Sackur, J., and Dupoux, E. (2010). How rich is consciousness? The partial awareness hypothesis. Trends in cognitive sciences, 14(7):301–307.

    Kozachkov, L., Lundqvist, M., Slotine, J.-J., and Miller, E. K. (2020). Achieving stable dynamics in neural circuits. PLoS computational biology, 16(8):e1007659.

    Kriegeskorte, N. (2015). Deep neural networks: a new framework for modeling biological vision and brain information processing. Annual review of vision science, 1:417–446.

    Krueger, K. A. and Dayan, P. (2009). Flexible shaping: How learning in small steps helps. Cognition, 110(3):380–394.

    Kruger, J., Wirtz, D., Van Boven, L., and Altermatt, T. W. (2004). The effort heuristic. Journal of Experimental Social Psychology, 40(1):91–98.

    Kurth-Nelson, Z., Economides, M., Dolan, R. J., and Dayan, P. (2016). Fast sequences of non-spatial state representations in humans. Neuron, 91(1):194–204.

    Kuyken, W., Watkins, E., Holden, E., White, K., Taylor, R. S., Byford, S., Evans, A., Radford, S., Teasdale, J. D., and Dalgleish, T. (2010). How does mindfulness-based cognitive therapy work? Behaviour research and therapy, 48(11):1105–1112.

    Kwapis, J. L., Jarome, T. J., and Helmstetter, F. J. (2015). The role of the medial prefrontal cortex in trace fear extinction. Learning & Memory, 22(1):39–46.

    Kyabgon, T. (2015). Moonbeams of Mahamudra. Carlton North: Shogam Publications.

    Lake, B. M., Salakhutdinov, R., and Tenenbaum, J. B. (2015). Human-level concept learning through probabilistic program induction. Science, 350(6266):1332–1338.

    Lambie, G. W. and Haugen, J. S. (2019). Understanding greed as a unified construct. Personality and Individual Differences, 141:31–39.

    Lamme, V. A. and Roelfsema, P. R. (2000). The distinct modes of vision offered by feedforward and recurrent processing. Trends in neurosciences, 23(11):571–579.

    Lao, S.-A., Kissane, D., and Meadows, G. (2016). Cognitive effects of mbsr/mbct: A systematic review of neuropsychological outcomes. Consciousness and cognition, 45:109–123.

    Larsson, G., Maire, M., and Shakhnarovich, G. (2017). Colorization as a proxy task for visual understanding. In CVPR, volume 2, page8.

    Lau, H. and Rosenthal, D. (2011). Empirical support for higher-order theories of conscious awareness. Trends in cognitive sciences, 15(8):365–373.

    Lazarus, R. S. (1993). From psychological stress to the emotions: A history of changing outlooks. Annual review of psychology, 44(1):1–22.

    Lazarus, R. S. and Folkman, S. (1984). Stress, appraisal, and coping. Springer publishing company.

    LeDoux, J. E. and Pine, D. S. (2016). Using neuroscience to help understand fear and anxiety: a two-system framework. American Journal of Psychiatry, 173(11):1083–1093.

    Legenstein, R., Chase, S. M., Schwartz, A. B., and Maass, W. (2010). A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task. Journal of Neuroscience, 30(25):8400–8410.

    Legg, S. and Hutter, M. (2007). Universal intelligence: A definition of machine intelligence. Minds and Machines, 17(4):391–444.

    Leknes, S., Brooks, J. C., Wiech, K., and Tracey, I. (2008). Pain relief as an opponent process: a psychophysical investigation. European journal of neuroscience, 28(4):794–801.

    Leknes, S. and Tracey, I. (2008). A common neurobiology for pain and pleasure. Nature Reviews Neuroscience, 9(4):314–320.

    Lengyel, M. and Dayan, P. (2008). Hippocampal contributions to control: the third way. In Advances in neural information processing systems, pages 889–896.

    Libet, B., Gleason, C. A., Wright, E. W., and Pearl, D. K. (1983). Time of conscious intention to act in relation to onset of cerebral activity (readiness-potential) the unconscious initiation of a freely voluntary act. Brain, 106(3):623–642.

    Lieder, F. and Griffiths, T. L. (2020). Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences, 43.

    Lin, L. J. (1991). Programming robots using reinforcement learning and teaching. In AAAI, pages 781–786.

    Lindsay, E. K. and Creswell, J. D. (2017). Mechanisms of mindfulness training: Monitor and acceptance theory (MAT). Clinical Psychology Review, 51:48–59.

    Liu, Y.-Y., Slotine, J.-J., and Barabási, A.-L. (2011). Controllability of complex networks. Nature, 473(7346):167.

    Livneh, Y., Ramesh, R. N., Burgess, C. R., Levandowski, K. M., Madara, J. C., Fenselau, H., Goldey, G. J., Diaz, V. E., Jikomes, N., Resch, J. M., et al. (2017). Homeostatic circuits selectively gate food cue responses in insular cortex. Nature, 546(7660):611.

    Lu, H., Zou, Q., Gu, H., Raichle, M. E., Stein, E. A., and Yang, Y. (2012). Rat brains also have a default mode network. Proceedings of the National Academy of Sciences, 109(10):3979–3984.

    Lusthaus, D. (1998). Buddhism, Yogācāra school of. In Routledge Encyclopedia of Philosophy. Taylor and Francis.

    Lusthaus, D. (2013). What is and isn’t Yogācāra. Yogacara Buddhism Research Association.

    Lutz, A., Slagter, H. A., Dunne, J. D., and Davidson, R. J. (2008). Attention regulation and monitoring in meditation. Trends in cognitive sciences, 12(4):163–169.

    Lutz, A. and Thompson, E. (2003). Neurophenomenology integrating subjective experience and brain dynamics in the neuroscience of consciousness. Journal of consciousness studies, 10(9-10):31–52.

    Ly, C., Greb, A. C., Cameron, L. P., Wong, J. M., Barragan, E. V., Wilson, P. C., Burbach, K. F., Zarandi, S. S., Sood, A., Paddy, M. R., et al. (2018). Psychedelics promote structural and functional neural plasticity. Cell reports, 23(11):3170–3182.

    Lyubomirsky, S. (2010). Hedonic adaptation to positive and negative experiences. The Oxford handbook of stress, health, and coping.

    Ma, W. J., Kording, K. P., and Goldreich, D. (2022). Bayesian models of perception and action. MIT Press. In press.

    MacDonald, G. (2009). Social pain and hurt feelings. Cambridge handbook of personality psychology, pages 541–555.

    MacKenzie, M. J. and Baumeister, R. F. (2015). Self-regulatory strength and mindfulness. In Handbook of mindfulness and self-regulation, pages 95–105. Springer.

    Mahasi, S. (1996). Great Discourse on Not Self (Anattalakkhana Sutta). Bangkok: Buddhadhamma Foundation.

    Mahasi, S. (1999). A Discourse on Dependent Origination. Bangkok: Buddhadhamma Foundation.

    Mahasi, S. (2016). Manual of Insight. Simon & Schuster.

    Mai, V., Mani, K., and Paull, L. (2022). Sample efficient deep reinforcement learning via uncertainty estimation. arXiv preprint arXiv:2201.01666.

    Malt, B. C., Ross, B. H., and Murphy, G. L. (1995). Predicting features for members of natural categories when categorization is uncertain. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(3):646.

    Mancinelli, F., Roiser, J., and Dayan, P. (2021). Internality and the internalisation of failure: Evidence from a novel task. PLoS Computational Biology, 17(7):e1009134.

    Marchetti, I., Koster, E. H., Klinger, E., and Alloy, L. B. (2016). Spontaneous thought and vulnerability to mood disorders: the dark side of the wandering mind. Clinical Psychological Science, 4(5):835–857.

    Marchetti, I., Van de Putte, E., and Koster, E. H. (2014). Self-generated thoughts and depression: from daydreaming to depressive symptoms. Frontiers in human neuroscience, 8:131.

    Marek, S. and Dosenbach, N. U. (2018). The frontoparietal network: function, electrophysiology, and importance of individual precision mapping. Dialogues in clinical neuroscience, 20(2):133.

    Markov, I. L. (2014). Limits on fundamental limits to computation. Nature, 512(7513):147.

    Markram, H., Gerstner, W., and Sjöström, P. J. (2012). Spike-timing-dependent plasticity: a comprehensive overview. Frontiers in synaptic neuroscience, 4:2.

    Martela, F. (2020). A Wonderful Life: Insights on Finding a Meaningful Existence. HarperCollins.

    Martin, D., Fowlkes, C., Tal, D., and Malik, J. (2001). A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In Proc. 8th Int’l Conf. Computer Vision, volume 2, pages 416–423.

    Mates, B. (1996). The skeptic way: Sextus Empiricus’ outlines of Pyrrhonism. Oxford University Press.

    Mattar, M. G. and Daw, N. D. (2018). Prioritized memory access explains planning and hippocampal replay. Nature Neuroscience, 21(11):1609–1617.

    McCloskey, M. and Cohen, N. J. (1989). Catastrophic interference in connectionist networks: The sequential learning problem. In Psychology of learning and motivation, volume 24, pages 109–165. Elsevier.

    McCullough, M. and vanOyen-Witvliet, C. (2002). The psychology of forgiveness. In Snyder, C. and Lopez, S., editors, The Oxford handbook of positive psychology. Oxford University Press.

    McDermott, D. (2007). Artificial intelligence and consciousness. The Cambridge handbook of consciousness, pages 117–150.

    McEvilley, T. (1982). Pyrrhonism and mādhyamika. Philosophy East and West, pages 3–35.

    Mee, S., Bunney, B. G., Reist, C., Potkin, S. G., and Bunney, W. E. (2006). Psychological pain: a review of evidence. Journal of Psychiatric Research, 40(8):680–690.

    Meerwijk, E. L. and Weiss, S. J. (2011). Toward a unifying definition of psychological pain. Journal of Loss and Trauma, 16(5):402–412.

    Mendel, J. M. (1995). Fuzzy logic systems for engineering: a tutorial. Proceedings of the IEEE, 83(3):345–377.

    Metzinger, T. (2003). Being no one. Cambridge, MA: MIT Press.

    Mikolov, T., Karafiát, M., Burget, L., Černockỳ, J., and Khudanpur, S. (2010). Recurrent neural network based language model. In Eleventh annual conference of the international speech communication association.

    Miller, R. R., Barnet, R. C., and Grahame, N. J. (1995). Assessment of the Rescorla–Wagner model. Psychological bulletin, 117(3):363.

    Minsky, M. (1988). Society of mind. Simon and Schuster.

    Minut, S. and Mahadevan, S. (2001). A reinforcement learning model of selective visual attention. In Proceedings of the fifth international conference on autonomous agents, pages 457–464. ACM.

    Mirolli, M. and Baldassarre, G. (2013). Intrinsically motivated learning in natural and artificial systems. Intrinsically Motivated Learning in Natural and Artificial Systems, pages 49–72.

    Misra, I., Zitnick, C. L., and Hebert, M. (2016). Shuffle and learn: unsupervised learning using temporal order verification. In European Conference on Computer Vision, pages 527–544. Springer.

    Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., and Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex ”frontal lobe” tasks: A latent variable analysis. Cognitive psychology, 41(1):49–100.

    Mnih, V., Heess, N., Graves, A., et al. (2014). Recurrent models of visual attention. In Advances in neural information processing systems, pages 2204–2212.

    Momennejad, I., Otto, A. R., Daw, N. D., and Norman, K. A. (2018). Offline replay supports planning in human reinforcement learning. eLife, e32548.

    Monti, M. M., Vanhaudenhuyse, A., Coleman, M. R., Boly, M., Pickard, J. D., Tshibanda, L., Owen, A. M., and Laureys, S. (2010). Willful modulation of brain activity in disorders of consciousness. New England Journal of Medicine, 362(7):579–589.

    Moore, A. W. and Atkeson, C. G. (1993). Prioritized sweeping: Reinforcement learning with less data and less time. Machine learning, 13(1):103–130.

    Moreno-Bote, R., Knill, D. C., and Pouget, A. (2011). Bayesian sampling in visual perception. Proceedings of the National Academy of Sciences, 108(30):12491–12496.

    Morison, B. (2019). Sextus Empiricus. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Mulder, J. M. (2018). Why intentions? Ratio, 31:51–64.

    Murphy, G. L. and Ross, B. H. (2010). Uncertainty in category-based induction: When do people integrate across categories? Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(2):263.

    Nakayama, K. (1999). Mid-level vision. The MIT encylopedia of the cognitive sciences.

    Nau, D. S., Au, T.-C., Ilghami, O., Kuter, U., Murdock, J. W., Wu, D., and Yaman, F. (2003). SHOP2: an HTN planning system. Journal of artificial intelligence research, 20:379–404.

    Neff, K. D., Kirkpatrick, K. L., and Rude, S. S. (2007). Self-compassion and adaptive psychological functioning. Journal of research in personality, 41(1):139–154.

    Nesse, R. M. (2000). Is depression an adaptation? Archives of General Psychiatry, 57(1):14–20.

    Nevin, J. A. (1999). Analyzing Thorndike’s law of effect: The question of stimulus-response bonds. Journal of the experimental analysis of behavior, 72(3):447–450.

    Ng, A. Y., Harada, D., and Russell, S. (1999). Policy invariance under reward transformations: Theory and application to reward shaping. In Icml, volume 99, pages 278–287.

    NIDA (2020). How does cocaine produce its effects? National Institute on Drug Abuse, retrieved from https://www.drugabuse.gov/publications/research-reports/cocaine/how-does-cocaine-produce-its-effects, on 26 Oct 2021.

    Nisargadatta, M. (1982). Seeds of Consciousness. New York: Grove Press.

    Niv, Y. (2009). Reinforcement learning in the brain. Journal of Mathematical Psychology, 53(3):139–154.

    Nokia, M. S., Lensu, S., Ahtiainen, J. P., Johansson, P. P., Koch, L. G., Britton, S. L., and Kainulainen, H. (2016). Physical exercise increases adult hippocampal neurogenesis in male rats provided it is aerobic and sustained. The Journal of physiology, 594(7):1855–1873.

    Nowak, A., Gelfand, M. J., Borkowski, W., Cohen, D., and Hernandez, I. (2016). The evolutionary basis of honor cultures. Psychological science, 27(1):12–24.

    Nowak, M. A., Tarnita, C. E., and Wilson, E. O. (2010). The evolution of eusociality. Nature, 466(7310):1057.

    Nummenmaa, L., Glerean, E., Hari, R., and Hietanen, J. K. (2014). Bodily maps of emotions. Proceedings of the National Academy of Sciences, 111(2):646–651.

    Nummenmaa, L., Glerean, E., Viinikainen, M., Jääskeläinen, I. P., Hari, R., and Sams, M. (2012). Emotions promote social interaction by synchronizing brain activity across individuals. Proceedings of the National Academy of Sciences, 109(24):9599–9604.

    Nutt, D. J., Lingford-Hughes, A., Erritzoe, D., and Stokes, P. R. (2015). The dopamine theory of addiction: 40 years of highs and lows. Nature Reviews Neuroscience, 16(5):305.

    Oatley, K. and Johnson-Laird, P. N. (1987). Towards a cognitive theory of emotions. Cognition and emotion, 1(1):29–50.

    Oatley, K. and Johnson-Laird, P. N. (1990). Semantic primitives for emotions: A reply to Ortony and Clore. Cognition and Emotion, 4(2):129–143.

    Oja, E. (1982). Simplified neuron model as a principal component analyzer. Journal of mathematical biology, 15(3):267–273.

    Oja, E. (1992). Principal components, minor components, and linear neural networks. Neural networks, 5(6):927–935.

    Oldmeadow, H. (1997). Delivering the last blade of grass: Aspects of the bodhisattva ideal in the mahāyāna. Asian Philosophy, 7(3):181–194.

    Olshausen, B. A. and Field, D. J. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381(6583):607.

    OpenAI (2018). OpenAI Five. https://blog.openai.com/openai-five/.

    Orbach, I., Mikulincer, M., Sirota, P., and Gilboa-Schechtman, E. (2003). Mental pain: a multidimensional operationalization and definition. Suicide and Life-Threatening Behavior, 33(3):219–230.

    O’Reilly, R. C., Hazy, T. E., Mollick, J., Mackie, P., and Herd, S. (2014). Goal-driven cognition in the brain: a computational framework. arXiv preprint, arXiv:1404.7591.

    Ottaviani, C., Shapiro, D., and Couyoumdjian, A. (2013). Flexibility as the key for somatic health: From mind wandering to perseverative cognition. Biological psychology, 94(1):38–43.

    Palmwood, E. N. and McBride, C. A. (2019). Challenge vs. threat: The effect of appraisal type on resource depletion. Current Psychology, 38(6):1522–1529.

    Pan, S. J. and Yang, Q. (2009). A survey on transfer learning. IEEE Transactions on knowledge and data engineering, 22(10):1345–1359.

    Papies, E. K. and Barsalou, L. W. (2015). Grounding desire and motivated behavior: A theoretical framework and review of empirical evidence. The psychology of desire, pages 36–60.

    Papini, M. R., Fuchs, P. N., and Torres, C. (2015). Behavioral neuroscience of psychological pain. Neuroscience & Biobehavioral Reviews, 48:53–69.

    Parker, G. A. and Smith, J. M. (1990). Optimality theory in evolutionary biology. Nature, 348(6296):27.

    Pascanu, R., Li, Y., Vinyals, O., Heess, N., Buesing, L., Racaničre, S., Reichert, D., Weber, T., Wierstra, D., and Battaglia, P. (2017). Learning model-based planning from scratch. arXiv preprint, arXiv:1707.06170.

    Pascual-Leone, A., Amedi, A., Fregni, F., and Merabet, L. B. (2005). The plastic human brain cortex. Annu. Rev. Neurosci., 28:377–401.

    Pathak, D., Agrawal, P., Efros, A. A., and Darrell, T. (2017). Curiosity-driven exploration by self-supervised prediction. In International Conference on Machine Learning (ICML).

    Peacock, J. (2018). Vedanā, ethics and character: A prolegomena. Contemporary Buddhism, 19(1):160–184.

    Pearl, J. (2009). Causality. Cambridge University Press.

    Peralta, V. and Cuesta, M. J. (2001). How many and which are the psychopathological dimensions in schizophrenia? Issues influencing their ascertainment. Schizophrenia research, 49(3):269–285.

    Perea, G., Navarrete, M., and Araque, A. (2009). Tripartite synapses: astrocytes process and control synaptic information. Trends in neurosciences, 32(8):421–431.

    Peters, J., Janzing, D., and Schölkopf, B. (2017). Elements of causal inference: foundations and learning algorithms. The MIT Press.

    Peters, J., Mülling, K., Kober, J., Nguyen-Tuong, D., and Krömer, O. (2011). Towards motor skill learning for robotics. In Robotics Research, pages 469–482. Springer.

    Peterson, C. (1999). Personal control and well-being. In Well-being: Foundations of hedonic psychology. Russell Sage Foundation.

    Pfeiffer, B. E. and Foster, D. J. (2013). Hippocampal place-cell sequences depict future paths to remembered goals. Nature, 497(7447):74–79.

    Pinker, S. (1999). How the mind works. Annals of the New York Academy of Sciences, 882(1):119–127.

    Pisella, L., Rode, G., Farne, A., Tilikete, C., and Rossetti, Y. (2006). Prism adaptation in the rehabilitation of patients with visuo-spatial cognitive disorders. Current opinion in neurology, 19(6):534–542.

    Platt, M. L. and Huettel, S. A. (2008). Risky business: the neuroeconomics of decision making under uncertainty. Nature neuroscience, 11(4):398.

    Pockett, S., Banks, W. P., and Gallagher, S., editors (2009). Does consciousness cause behavior? MIT Press.

    Poerio, G. L., Totterdell, P., Emerson, L.-M., and Miles, E. (2015). Love is the triumph of the imagination: Daydreams about significant others are associated with increased happiness, love and connection. Consciousness and Cognition, 33:135–144.

    Poerio, G. L., Totterdell, P., and Miles, E. (2013). Mind-wandering and negative mood: Does one thing really lead to another? Consciousness and cognition, 22(4):1412–1421.

    Poole, D. L. and Mackworth, A. K. (2010). Artificial Intelligence: foundations of computational agents. Cambridge University Press. Free online at https://artint.info/2e/.

    Pramote, P. (2013). A Path to Enlightenment I. Prima Publishing: Bangkok.

    Prebble, S. C., Addis, D. R., and Tippett, L. J. (2013). Autobiographical memory and sense of self. Psychological bulletin, 139(4):815.

    Proust, J. (2010). Metacognition. Philosophy Compass, 5(11):989–998.

    Quiroga, R. Q., Kreiman, G., Koch, C., and Fried, I. (2008). Sparse but not ’grandmother-cell’ coding in the medial temporal lobe. Trends in cognitive sciences, 12(3):87–91.

    Quiroga, R. Q., Reddy, L., Kreiman, G., Koch, C., and Fried, I. (2005). Invariant visual representation by single neurons in the human brain. Nature, 435(7045):1102.

    Raffaeli, W. and Arnaudo, E. (2017). Pain as a disease: an overview. Journal of pain research, 10:2003.

    Raichle, M. E. (2015). The brain’s default mode network. Annual review of neuroscience, 38:433–447.

    Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., and Shulman, G. L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences, 98(2):676–682.

    Raja, S. N., Carr, D. B., Cohen, M., Finnerup, N. B., Flor, H., Gibson, S., Keefe, F. J., Mogil, J. S., Ringkamp, M., Sluka, K. A., et al. (2020). The revised international association for the study of pain definition of pain: concepts, challenges, and compromises. Pain, 161(9):1976–1982.

    Rao, A. S. and Georgeff, M. P. (1991). Modeling rational agents within a BDI-architecture. KR, 91:473–484.

    Recht, B., Re, C., Wright, S., and Niu, F. (2011). Hogwild: A lock-free approach to parallelizing stochastic gradient descent. In Advances in neural information processing systems, pages 693–701.

    Recht, B., Roelofs, R., Schmidt, L., and Shankar, V. (2019). Do imagenet classifiers generalize to imagenet? In International Conference on Machine Learning, pages 5389–5400. PMLR.

    Redgrave, P. and Gurney, K. (2006). The short-latency dopamine signal: a role in discovering novel actions? Nature reviews neuroscience, 7(12):967.

    Redshaw, J. and Bulley, A. (2018). Future-thinking in animals. The psychology of thinking about the future, page31.

    Reggia, J. A. (2013). The rise of machine consciousness: Studying consciousness with computational models. Neural Networks, 44:112–131.

    Revonsuo, A. (2000). The reinterpretation of dreams: An evolutionary hypothesis of the function of dreaming. Behavioral and Brain Sciences, 23(6):877–901.

    Roese, N. J. (1997). Counterfactual thinking. Psychological bulletin, 121(1):133.

    Rosch, E. (1978). Principles of categorization. Cognition and categorization.

    Rosch, E. (1999). Reclaiming concepts. Journal of consciousness studies, 6(11-12):61–77.

    Rosenberg, A. and Bouchard, F. (2011). Fitness. In Zalta, E. N., editor, Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Roskies, A. (2006). Neuroscientific challenges to free will and responsibility. Trends in cognitive sciences, 10(9):419–423.

    Ruby, F. J. M., Smallwood, J., Engen, H., and Singer, T. (2013). How self-generated thought shapes mood — the relation between mind-wandering and mood depends on the socio-temporal content of thoughts. PLoS ONE, 8(10):1–7.

    Rueda, M. R., Posner, M. I., and Rothbart, M. K. (2004). Attentional control and self-regulation. Handbook of self-regulation: Research, theory, and applications, 2:284–299.

    Russell, S. and Norvig, P. (2020). Artificial intelligence: a modern approach. Pearson Education, 4th edition.

    Russell, S. J. (1997). Rationality and intelligence. Artificial intelligence, 94(1-2):57–77.

    Rutledge, R. B., De Berker, A. O., Espenhahn, S., Dayan, P., and Dolan, R. J. (2016). The social contingency of momentary subjective well-being. Nature Communications, 7:11825.

    Rutledge, R. B., Skandali, N., Dayan, P., and Dolan, R. J. (2014). A computational and neural model of momentary subjective well-being. Proceedings of the National Academy of Sciences, 111(33):12252–12257.

    Safran, J. and Segal, Z. V. (1990). Interpersonal process in cognitive therapy. Jason Aronson, Inc.

    Sagi, D. (2011). Perceptual learning in vision research. Vision research, 51(13):1552–1566.

    Sale, A., Vetencourt, J. F. M., Medini, P., Cenni, M. C., Baroncelli, L., De Pasquale, R., and Maffei, L. (2007). Environmental enrichment in adulthood promotes amblyopia recovery through a reduction of intracortical inhibition. Nature neuroscience, 10(6):679.

    Salimans, T., Ho, J., Chen, X., Sidor, S., and Sutskever, I. (2017). Evolution strategies as a scalable alternative to reinforcement learning. arXiv preprint, arXiv:1703.03864.

    Salzberg, S. (2002). Lovingkindness: The revolutionary art of happiness. Shambhala Publications.

    Samuel, A. (1959). Some studies in machine learning using the game of checkers. IBM J. of Research and Development, 3:210–229.

    Sapolsky, R. M. (2004). Why zebras don’t get ulcers. Holt paperbacks, 2nd edition.

    Schaal, S. (1999). Is imitation learning the route to humanoid robots? Trends in cognitive sciences, 3(6):233–242.

    Schaul, T., Quan, J., Antonoglou, I., and Silver, D. (2016). Prioritized experience replay. In International Conference on Learning Representations.

    Scherer, K. R. (2009). The dynamic architecture of emotion: Evidence for the component process model. Cognition and emotion, 23(7):1307–1351.

    Scherer, K. R. (2011). On the rationality of emotions: or, when are emotions rational? Social Science Information, 50(3-4):330–350.

    Schmidhuber, J. (1991). Curious model-building control systems. In Neural Networks, 1991. 1991 IEEE International Joint Conference on, pages 1458–1463. IEEE.

    Schooler, J. W., Smallwood, J., Christoff, K., Handy, T. C., Reichle, E. D., and Sayette, M. A. (2011). Meta-awareness, perceptual decoupling and the wandering mind. Trends in cognitive sciences, 15(7):319–326.

    Schroeder, J. W. (2004). Skillful means: The heart of Buddhist compassion, volume 54. Motilal Banarsidass Publ.

    Schroeder, T. (2017). Desire. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Schultz, W. (2016). Dopamine reward prediction error coding. Dialogues in clinical neuroscience, 18(1):23.

    Schwartz, B. (2004). The paradox of choice: Why more is less. New York: HarperCollins.

    Sebastian, C., Burnett, S., and Blakemore, S.-J. (2008). Development of the self-concept during adolescence. Trends in cognitive sciences, 12(11):441–446.

    Seth, A. (2009). Functions of consciousness. In Banks, W., editor, Encyclopedia of Consciousness, volume 1, pages 279–293. Elsevier Press.

    Seth, A. K., Baars, B. J., and Edelman, D. B. (2005). Criteria for consciousness in humans and other mammals. Consciousness and cognition, 14(1):119–139.

    Seth, A. K. and Tsakiris, M. (2018). Being a beast machine: the somatic basis of selfhood. Trends in cognitive sciences, 22(11):969–981.

    Seymour, B. (2019). Pain: a precision signal for reinforcement learning and control. Neuron, 101(6):1029–1041.

    Seymour, B., O’doherty, J. P., Koltzenburg, M., Wiech, K., Frackowiak, R., Friston, K., and Dolan, R. (2005). Opponent appetitive-aversive neural processes underlie predictive learning of pain relief. Nature neuroscience, 8(9):1234–1240.

    Shapiro, S. L., Carlson, L. E., Astin, J. A., and Freedman, B. (2006). Mechanisms of mindfulness. Journal of clinical psychology, 62(3):373–386.

    Shulman, G. L., Fiez, J. A., Corbetta, M., Buckner, R. L., Miezin, F. M., Raichle, M. E., and Petersen, S. E. (1997). Common blood flow changes across visual tasks: II. decreases in cerebral cortex. Journal of cognitive neuroscience, 9(5):648–663.

    Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587):484.

    Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., et al. (2017). Mastering the game of Go without human knowledge. Nature, 550(7676):354.

    Simon, H. A. (1967). Motivational and emotional controls of cognition. Psychological review, 74(1):29.

    Simon, H. A. (1972). Theories of bounded rationality. Decision and organization, 1(1):161–176.

    Singer, A. C. and Frank, L. M. (2009). Rewarded outcomes enhance reactivation of experience in the hippocampus. Neuron, 64(6):910–921.

    Singer, T., Seymour, B., O’Doherty, J., Kaube, H., Dolan, R. J., and Frith, C. D. (2004). Empathy for pain involves the affective but not sensory components of pain. Science, 303(5661):1157–1162.

    Singh, P. (2012). Examining the society of mind. Computing and Informatics, 22(6):521–543.

    Singh, S., Lewis, R. L., and Barto, A. G. (2009). Where do rewards come from. In Proceedings of the annual conference of the cognitive science society, pages 2601–2606. Cognitive Science Society.

    Singh, S., Lewis, R. L., Barto, A. G., and Sorg, J. (2010). Intrinsically motivated reinforcement learning: An evolutionary perspective. IEEE Transactions on Autonomous Mental Development, 2(2):70–82.

    Skinner, E. A. (1996). A guide to constructs of control. Journal of personality and social psychology, 71(3):549.

    Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological bulletin, 119(1):3.

    Smallwood, J., Fitzgerald, A., Miles, L. K., and Phillips, L. H. (2009). Shifting moods, wandering minds: negative moods lead the mind to wander. Emotion, 9(2):271.

    Smallwood, J., McSpadden, M., and Schooler, J. W. (2007). The lights are on but no ones home: Meta-awareness and the decoupling of attention when the mind wanders. Psychonomic bulletin & review, 14(3):527–533.

    Smith, J. (2017). Self-consciousness. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University.

    Smith, J. M. and Price, G. R. (1973). The logic of animal conflict. Nature, 246(5427):15.

    Spence, S. A., Brooks, D. J., Hirsch, S. R., Liddle, P. F., Meehan, J., and Grasby, P. M. (1997). A pet study of voluntary movement in schizophrenic patients experiencing passivity phenomena (delusions of alien control). Brain: a journal of neurology, 120(11):1997–2011.

    Spira, R. (2017). The nature of consciousness. Oxford: Sahaja Publications.

    Spolidoro, M., Baroncelli, L., Putignano, E., Maya-Vetencourt, J. F., Viegi, A., and Maffei, L. (2011). Food restriction enhances visual cortex plasticity in adulthood. Nature Communications, 2:320.

    Sridharan, D., Levitin, D. J., and Menon, V. (2008). A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences, 105(34):12569–12574.

    Stanovich, K. E. (2004). The robot’s rebellion: Finding meaning in the age of Darwin. University of Chicago Press.

    Steels, L. (2008). The symbol grounding problem has been solved. So what’s next. Symbols and embodiment: Debates on meaning and cognition, pages 223–244.

    Stein, D., Kogan, C., Atmaca, M., Fineberg, N., Fontenelle, L., Grant, J., Matsunaga, H., Reddy, Y., Simpson, H., Thomsen, P., et al. (2016). The classification of obsessive–compulsive and related disorders in the ICD-11. Journal of Affective Disorders, 190:663–674.

    Sterzer, P., Kleinschmidt, A., and Rees, G. (2009). The neural bases of multistable perception. Trends in cognitive sciences, 13(7):310–318.

    Strawson, G. and Watson, G. (1998). Free will. In Routledge Encyclopedia of Philosophy. Taylor and Francis.

    Striker, G. (2004). Historical reflections on classical Pyrrhonism and neo-Pyrrhonism. In Sinnott-Armstrong, W., editor, Pyrrhonian Skepticism, pages 13–24. Oxford University Press.

    Su, G., Wei, D., Varshney, K. R., and Malioutov, D. M. (2015). Interpretable two-level boolean rule learning for classification. arXiv preprint, arXiv:1511.07361.

    Such, F. P., Madhavan, V., Conti, E., Lehman, J., Stanley, K. O., and Clune, J. (2017). Deep neuroevolution: genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning. arXiv preprint, arXiv:1712.06567.

    Sun, R., Slusarz, P., and Terry, C. (2005). The interaction of the explicit and the implicit in skill learning: A dual-process approach. Psychological review, 112(1):159.

    Sutton, R. S. (1991). Dyna, an integrated architecture for learning, planning, and reacting. ACM SIGART Bulletin, 2(4):160–163.

    Sutton, R. S. and Barto, A. G. (2018). Reinforcement learning: An introduction. MIT press: Cambridge, 2nd edition.

    Sutton, R. S., Precup, D., and Singh, S. (1999). Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artificial intelligence, 112(1-2):181–211.

    Svenaeus, F. (2014). The phenomenology of suffering in medicine and bioethics. Theoretical medicine and bioethics, 35(6):407–420.

    Tabor, A., Thacker, M. A., Moseley, G. L., and Körding, K. P. (2017). Pain: a statistical account. PLoS computational biology, 13(1):e1005142.

    Taddeo, M. and Floridi, L. (2005). Solving the symbol grounding problem: a critical review of fifteen years of research. Journal of Experimental & Theoretical Artificial Intelligence, 17(4):419–445.

    Tagawa, S. (2009). Living Yogcra: An introduction to consciousness-only Buddhism. Simon and Schuster. Translated by Charles Muller.

    Takahashi, Y. K., Batchelor, H. M., Liu, B., Khanna, A., Morales, M., and Schoenbaum, G. (2017). Dopamine neurons respond to errors in the prediction of sensory features of expected rewards. Neuron, 95(6):1395–1405.

    Tamar, A., Wu, Y., Thomas, G., Levine, S., and Abbeel, P. (2016). Value iteration networks. In Advances in Neural Information Processing Systems, pages 2154–2162.

    Tan, S., Caruana, R., Hooker, G., and Lou, Y. (2017). Detecting bias in black-box models using transparent model distillation. arXiv preprint, arXiv:1710.06169.

    Tanaka, K. (1996). Inferotemporal cortex and object vision. Annual review of neuroscience, 19(1):109–139.

    Tate, T. and Pearlman, R. (2019). What we mean when we talk about suffering–and why Eric Cassell should not have the last word. Perspectives in biology and medicine, 62(1):95–110.

    Teasdale, J. D. (1999). Metacognition, mindfulness and the modification of mood disorders. Clinical Psychology & Psychotherapy, 6(2):146–155.

    Teasdale, J. D. and Chaskalson, M. (2011a). How does mindfulness transform suffering? I: The nature and origins of dukkha. Contemporary Buddhism, 12(01):89–102.

    Teasdale, J. D. and Chaskalson, M. (2011b). How does mindfulness transform suffering? II: the transformation of dukkha. Contemporary Buddhism, 12(1):103–124.

    Teasdale, J. D., Segal, Z. V., Williams, J. M. G., Ridgeway, V. A., Soulsby, J. M., and Lau, M. A. (2000). Prevention of relapse/recurrence in major depression by mindfulness-based cognitive therapy. Journal of consulting and clinical psychology, 68(4):615.

    Tejaniya, A. (2008). Awareness alone is not enough. Selangor: Auspicious Affinity.

    Teper, R. and Inzlicht, M. (2013). Meditation, mindfulness and executive control: the importance of emotional acceptance and brain-based performance monitoring. Social cognitive and affective neuroscience, 8(1):85–92.

    Tesauro, G. (1995). Temporal difference learning and TD-gammon. Communications of the ACM, 38(3):58–68.

    Theis, T. N. and Wong, H.-S. P. (2017). The end of Moore’s law: A new beginning for information technology. Computing in Science & Engineering, 19(2):41–50.

    Thierry, B., Steru, L., Chermat, R., and Simon, P. (1984). Searching-waiting strategy: A candidate for an evolutionary model of depression? Behavioral and neural biology, 41(2):180–189.

    Thrun, S. and Pratt, L., editors (2012). Learning to learn. Springer: New York.

    Toda, K. and Platt, M. L. (2015). Animal cognition: monkeys pass the mirror test. Current Biology, 25(2):R64–R66.

    Toivonen, H. and Gross, O. (2015). Data mining and machine learning in computational creativity. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 5(6):265–275.

    Tononi, G. and Edelman, G. M. (1998). Consciousness and complexity. Science, 282(5395):1846–1851.

    Tossani, E. (2013). The concept of mental pain. Psychotherapy and psychosomatics, 82(2):67–73.

    Tsakiris, M., Hesse, M. D., Boy, C., Haggard, P., and Fink, G. R. (2007). Neural signatures of body ownership: a sensory network for bodily self-consciousness. Cerebral cortex, 17(10):2235–2244.

    Tversky, A. and Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157):1124–1131.

    Vago, D. R. and David, S. A. (2012). Self-awareness, self-regulation, and self-transcendence (S-ART): A framework for understanding the neurobiological mechanisms of mindfulness. Frontiers in human neuroscience, 6:296.

    Van Boven, L. (2005). Experientialism, materialism, and the pursuit of happiness. Review of general psychology, 9(2):132–142.

    Van Gulick, R. (2021). Consciousness. In Zalta, E. N., editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University, Winter 2021 edition.

    Van Hateren, J. H. and van der Schaaf, A. (1998). Independent component filters of natural images compared with simple cells in primary visual cortex. Proceedings of the Royal Society of London. Series B: Biological Sciences, 265(1394):359–366.

    Van Hooft, S. (1998). Suffering and the goals of medicine. Medicine, Health Care and Philosophy, 1(2):125–131.

    van Vugt, M. K., Taatgen, N. A., Sackur, J., Bastian, M., Borst, J., and Mehlhorn, K. (2015). Modeling mind-wandering: a tool to better understand distraction. In Proceedings of the 13th International Conference on Cognitive Modeling, pages 252–257. University of Groningen Groningen, Netherlands.

    Van Vugt, M. K., van der Velde, M., and ESM-MERGE Investigators (2018). How does rumination impact cognition? A first mechanistic model. Topics in Cognitive Science, 10(1):175–191.

    Veehof, M. M., Trompetter, H., Bohlmeijer, E. T., and Schreurs, K. M. G. (2016). Acceptance-and mindfulness-based interventions for the treatment of chronic pain: a meta-analytic review. Cognitive behaviour therapy, 45(1):5–31.

    Verduyn, P., Lee, D. S., Park, J., Shablack, H., Orvell, A., Bayer, J., Ybarra, O., Jonides, J., and Kross, E. (2015). Passive facebook usage undermines affective well-being: Experimental and longitudinal evidence. Journal of Experimental Psychology: General, 144(2):480.

    Verhaeghen, P. (2017). The self-effacing Buddhist: No(t)-self in early Buddhism and contemplative neuroscience. Contemporary Buddhism, 18(1):21–36.

    Vetencourt, J. F. M., Sale, A., Viegi, A., Baroncelli, L., De Pasquale, R., O’Leary, O. F., Castrén, E., and Maffei, L. (2008). The antidepressant fluoxetine restores plasticity in the adult visual cortex. Science, 320(5874):385–388.

    Vincent, P., Larochelle, H., Bengio, Y., and Manzagol, P.-A. (2008). Extracting and composing robust features with denoising autoencoders. In Proceedings of the 25th International Conference on Machine learning, pages 1096–1103.

    Vohs, K. D. and Schooler, J. W. (2008). The value of believing in free will: Encouraging a belief in determinism increases cheating. Psychological science, 19(1):49–54.

    Von Neumann, J. and Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.

    Wager, T. D., Atlas, L. Y., Botvinick, M. M., Chang, L. J., Coghill, R. C., Davis, K. D., Iannetti, G. D., Poldrack, R. A., Shackman, A. J., and Yarkoni, T. (2016). Pain in the acc? Proceedings of the National Academy of Sciences, 113(18):E2474–E2475.

    Wagner, K., Reggia, J. A., Uriagereka, J., and Wilkinson, G. S. (2003). Progress in the simulation of emergent communication and language. Adaptive Behavior, 11(1):37–69.

    Walter, S. (2009). Epiphenomenalism. In Encyclopedia of neuroscience, pages 1137–1139. Springer.

    Watkins, E. and Teasdale, J. D. (2004). Adaptive and maladaptive self-focus in depression. Journal of affective disorders, 82(1):1–8.

    Wegner, D. M. (2002). The illusion of conscious will. Cambridge, MA: MIT Press.

    Wegner, D. M. (2003). The mind’s best trick: how we experience conscious will. Trends in cognitive sciences, 7(2):65–69.

    Weike, A. I., Schupp, H. T., and Hamm, A. O. (2007). Fear acquisition requires awareness in trace but not delay conditioning. Psychophysiology, 44(1):170–180.

    Weiss, K., Khoshgoftaar, T. M., and Wang, D. (2016). A survey of transfer learning. Journal of Big data, 3(1):9.

    Wen, W. and Haggard, P. (2018). Control changes the way we look at the world. Journal of cognitive neuroscience.

    Westbrook, R. F., Iordanova, M., McNally, G., Richardson, R., and Harris, J. A. (2002). Reinstatement of fear to an extinguished conditioned stimulus: two roles for context. Journal of Experimental Psychology: Animal Behavior Processes, 28(1):97.

    Whiten, A., McGuigan, N., Marshall-Pescini, S., and Hopper, L. M. (2009). Emulation, imitation, over-imitation and the scope of culture for child and chimpanzee. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1528):2417–2428.

    Whitmer, A. J. and Gotlib, I. H. (2013). An attentional scope model of rumination. Psychological bulletin, 139(5):1036.

    Wiech, K., Ploner, M., and Tracey, I. (2008). Neurocognitive aspects of pain perception. Trends in cognitive sciences, 12(8):306–313.

    Wielgosz, J., Goldberg, S. B., Kral, T. R., Dunne, J. D., and Davidson, R. J. (2019). Mindfulness meditation and psychopathology. Annual review of clinical psychology, 15:285–316.

    Wikenheiser, A. M. and Redish, A. D. (2015). Hippocampal theta sequences reflect current goals. Nature Neuroscience, 18(2):289–294.

    Williams, J. M. G. (2008a). Mindfulness, depression and modes of mind. Cognitive Therapy and Research, 32(6):721.

    Williams, P. (2008b). Mahayana Buddhism: The Doctrinal Foundations. Routledge.

    Wolpert, D. M., Miall, R. C., and Kawato, M. (1998). Internal models in the cerebellum. Trends in cognitive sciences, 2(9):338–347.

    Wong, R. O. (1999). Retinal waves and visual system development. Annual review of neuroscience, 22(1):29–47.

    Wright, A. (2011). A criticism of the IASP’s definition of pain. Journal of Consciousness Studies, 18(9-10):19–44.

    Wright, R. (1994). The Moral Animal. Vintage Books.

    Wright, R. (2017). Why Buddhism is true: The science and philosophy of meditation and enlightenment. Simon and Schuster.

    Xu, D., Li, T., Li, Y., Su, X., Tarkoma, S., Jiang, T., Crowcroft, J., and Hui, P. (2020). Edge intelligence: Architectures, challenges, and applications. arXiv preprint, arXiv:2003.12172.

    Yehuda, R. (2002). Post-traumatic stress disorder. New England journal of medicine, 346(2):108–114.

    Yi, K., Wu, J., Gan, C., Torralba, A., Kohli, P., and Tenenbaum, J. (2018). Neural-symbolic VQA: Disentangling reasoning from vision and language understanding. In Advances in Neural Information Processing Systems, pages 1031–1042.

    Yoshida, W., Seymour, B., Koltzenburg, M., and Dolan, R. J. (2013). Uncertainty increases pain: evidence for a novel mechanism of pain modulation involving the periaqueductal gray. Journal of Neuroscience, 33(13):5638–5646.

    Zeng, J., Ustun, B., and Rudin, C. (2017). Interpretable classification models for recidivism prediction. Journal of the Royal Statistical Society: Series A (Statistics in Society), 180(3):689–722.

    Zenke, F., Gerstner, W., and Ganguli, S. (2017). The temporal paradox of hebbian learning and homeostatic plasticity. Current opinion in neurobiology, 43:166–176.

    Zhang, K. and Sejnowski, T. J. (2000). A universal scaling law between gray matter and white matter of cerebral cortex. Proceedings of the National Academy of Sciences, 97(10):5621–5626.

    Zhang, R., Brennan, T. J., and Lo, A. W. (2014). The origin of risk aversion. Proceedings of the National Academy of Sciences, 111(50):17777–17782.

    Zhou, B., Zhao, H., Puig, X., Xiao, T., Fidler, S., Barriuso, A., and Torralba, A. (2019). Semantic understanding of scenes through the ADE20K dataset. International Journal of Computer Vision, 127(3):302–321.

    Zhuang, C., Yan, S., Nayebi, A., Schrimpf, M., Frank, M. C., DiCarlo, J. J., and Yamins, D. L. (2021). Unsupervised neural network models of the ventral visual stream. Proceedings of the National Academy of Sciences, 118(3).

    Ziemke, T. (2007). The embodied self: Theories, hunches and robot models. Journal of Consciousness Studies, 14(7):167–179.

    Zinkevich, M., Johanson, M., Bowling, M., and Piccione, C. (2008). Regret minimization in games with incomplete information. In Advances in neural information processing systems, pages 1729–1736.

    Zinkevich, M., Weimer, M., Li, L., and Smola, A. J. (2010). Parallelized stochastic gradient descent. In Advances in neural information processing systems, pages 2595–2603.