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Human consciousness is fundamental for perception and highest emotions

Published online by Cambridge University Press:  24 November 2016

Leonid Perlovsky*
Affiliation:
Psychology Department, Northeastern University, Boston, MA 02115. lperl@rcn.comhttp://www.leonid-perlovsky.com/

Abstract

Have Morsella et al. examined the fundamentals of consciousness? An experiment by Bar et al. (2006) has demonstrated the fundamental aspects of conscious and unconscious mechanisms of perception. The mental representations are not crisp and conscious like the perceived objects are, but vague and unconscious. This experiment points to the fundamental function of the neural mechanisms of consciousness in perception. Consciousness is also fundamental for the highest emotions.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2016 

I very much appreciate the Morsella et al.'s desire to follow an example set by physics and begin “with the examination of the most basic, elemental instantiation of the phenomenon of interest” (sect. 1.3, para. 1). However, I would question how successfully this intent has been realized. A conceptually simple experiment by Bar et al. (Reference Bar, Kassam, Ghuman, Boshyan, Schmid, Dale, Hämäläinen, Marinkovic, Schacter, Rosen and Halgren2006) has demonstrated the fundamental aspects of conscious and unconscious mechanisms of perception. The mental representations of even simple everyday objects are not crisp and conscious like the perceived objects are, but vague and unconscious. This experiment identifies and illuminates the conceptual framework, as well as the purpose and the fundamental aspect of the neural mechanisms of consciousness in perception (Perlovsky Reference Perlovsky2009).

Perception of events in the world is based on mental representations (Grossberg Reference Grossberg1988; Kosslyn Reference Kosslyn1980). Adapting representations to reality therefore is a condition of survival. Correspondingly, humans have an instinctual drive for developing adequate representations. A theory of this drive (Perlovsky Reference Perlovsky2006; Reference Perlovsky, Perlovsky and Kozma2007; Reference Perlovsky2014a; Reference Perlovsky2015) is based on Grossberg and Levine's (Reference Grossberg and Levine1987) theory of drives and emotions. According to Grossberg and Levine, the mechanisms of drives include biological mechanisms similar to sensors measuring vital bodily parameters. If a vital parameter is outside of its safe range, neural signals indicate this to the decision-making parts of the brain. These neural signals and corresponding states of mind are perceived internally as emotions. The extension of this theory to developing representations (Perlovsky Reference Perlovsky2006; Reference Perlovsky, Perlovsky and Kozma2007; Reference Perlovsky2014a; Reference Perlovsky2015) has suggested the existence of a mechanism measuring similarities between mental representations and events in sensory data, or more generally, similarities between bottom-up and top-down signals. This mechanism is called the “knowledge instinct”; its neural mechanism – involving dorsolateral prefrontal cortex, orbitofrontal cortex, striatum, opioids, and dopamine – is outlined in Levine (Reference Levine2012).

The fundamental aspects of conscious and unconscious mechanisms of the neural operations of the knowledge instinct are characterized by a process of “from vague to crisp” representations. This has been confirmed in Bar et al. (Reference Bar, Kassam, Ghuman, Boshyan, Schmid, Dale, Hämäläinen, Marinkovic, Schacter, Rosen and Halgren2006), which identifies the neural mechanisms of consciousness in perception (Perlovsky Reference Perlovsky2009). Bar et al. have demonstrated that a process “from vague to crisp” takes approximately 0.6 sec (hundreds of neural operations), and the major part of this process is inaccessible to consciousness. Only in the moment when a representation matches an object's projection (from the retina) on the visual cortex does the representation become clear-crisp and conscious. The knowledge instinct operations become accessible to consciousness at the end of the unconscious process “from vague to crisp”; therefore, the conscious perception is a small part of the entire perception process (Bar et al. Reference Bar, Kassam, Ghuman, Boshyan, Schmid, Dale, Hämäläinen, Marinkovic, Schacter, Rosen and Halgren2006).

Why does “simple” object perception require such a complex operation, involving conscious, unconscious, vague, and crisp representations? The answer to this question can only be understood after decades of mathematical modeling of this process, which reveal the role of the conscious and unconscious. Mathematical psychologists modeling the process of perception, as well as artificial intelligence engineers developing robots with visual perception abilities, have been failing since the 1950s. Recently, the past decades of failures have been understood to be due to the logical models employed. Only the logical part of the perception processes is accessible to consciousness and has inspired the development of these past mathematical models. However, because the vague processes are not accessible to consciousness, their operations have not been noticed or understood and have been missed in the mathematical models (Perlovsky Reference Perlovsky2001). As it turns out, the models required for matching bottom-up and top-down signals based on logic require a number of computations larger than the interactions between all of the elementary particles in the entire life of the universe (Perlovsky Reference Perlovsky1998).

This complexity is a fundamental fact related to the Gödelian inconsistency of logic (Perlovsky Reference Perlovsky2013c), which is considered to be one of the most fundamental mathematical results of the twentieth century. The complexity has been overcome when the representations and the entire processes of matching bottom-up and top-down signals are modeled as processes “from vague to crisp” described by dynamic logic (Perlovsky Reference Perlovsky2006; Reference Perlovsky, Perlovsky and Kozma2007; Reference Perlovsky2013c). This mathematical model has been confirmed in (Bar et al. Reference Bar, Kassam, Ghuman, Boshyan, Schmid, Dale, Hämäläinen, Marinkovic, Schacter, Rosen and Halgren2006). Thus, unconscious “vague-to-crisp” processes are fundamental for perception, cognition, and the knowledge instinct; the clear-crisp and conscious part of these processes is only a small part. Let us repeat, the vague processes are not accessible to consciousness; if they were, perception and cognition would be mostly vague. The unconscious is needed so that we are not aware of the useless vague perceptions. Crisp and clear (“logical”) perception is a minor part of the perception process, but it is conscious (and therefore it biases our understanding toward logic); in our consciousness, we perceive a clear form of logic-like perceptions.

The knowledge instinct is similar to other drives in that its satisfaction is accompanied by emotional neural signals and states. These emotions related to knowledge are aesthetic emotions (Perlovsky Reference Perlovsky2014a). At lower levels of the mental hierarchy (perception of everyday objects), they are usually below the level of consciousness. At higher levels (cognition of abstract concepts), they could be conscious (existence of these emotions has been demonstrated experimentally in Perlovsky et al. [Reference Perlovsky, Bonniot-Cabanac and Cabanac2010]). Representations near the top of the hierarchy model an entire life's experience; they are mostly vague, unconscious, and vaguely perceived as the “meaning of life.” But the corresponding emotions could be conscious and perceived as emotions of the beautiful (Perlovsky Reference Perlovsky2010a; Schoeller Reference Schoeller2015; Schoeller & Perlovsky Reference Schoeller and Perlovsky2015). Usually, these are not well understood because of confusion between unconscious cognition and conscious language (Perlovsky Reference Perlovsky, Pereira and Lehmann2013a; Reference Perlovsky2013b). The knowledge instinct and the related aesthetic emotions explain the strong effects of musical emotions, their origins, their evolution, as well as their functions in cognition (Perlovsky Reference Perlovsky2010b; Reference Perlovsky2012a; Reference Perlovsky2012b; Reference Perlovsky2014b). The function of musical emotions is to help overcome cognitive dissonances and to keep contradictory cognitions in consciousness (Masataka & Perlovsky Reference Masataka and Perlovsky2012; Perlovsky Reference Perlovsky2015; Perlovsky et al. Reference Perlovsky, Cabanac, Bonniot-Cabanac and Cabanac2013).

In summary, the knowledge instinct addresses aspects of consciousness from the conscious perception of objects to the highest forms unique to humans, including the concepts of the meaning of life, emotions of the beautiful, and musical emotions. I do not see how skeletal consciousness can explain the functions of consciousness and unconsciousness revealed in Bar et al. (Reference Bar, Kassam, Ghuman, Boshyan, Schmid, Dale, Hämäläinen, Marinkovic, Schacter, Rosen and Halgren2006), and specifically human functions of consciousness related to music and the beautiful. The knowledge instinct is fundamental for survival in humans and animals, which have used mental representations for perception likely since amniotes onward. Skeletal consciousness does not seem to be specifically characteristic for humans or higher animals.

I would conclude that the analysis in the target article is far from straightforward; instead, it is convoluted and disguises rather than reveals the conceptual framework, the purpose, and the mechanisms of consciousness.

References

Bar, M., Kassam, K. S., Ghuman, A. S., Boshyan, J., Schmid, A. M., Dale, A. M., Hämäläinen, M. S., Marinkovic, K., Schacter, D. L., Rosen, B. R. & Halgren, E. (2006) Top-down facilitation of visual recognition. Proceedings of the National Academy of Sciences USA 103:449–54.CrossRefGoogle ScholarPubMed
Grossberg, S. (1988) Neural networks and natural intelligence. MIT Press.CrossRefGoogle Scholar
Grossberg, S. & Levine, D. S. (1987) Neural dynamics of attentionally modulated Pavlovian conditioning: Blocking, inter-stimulus interval, and secondary reinforcement. Psychobiology 15(3):195240.CrossRefGoogle Scholar
Kosslyn, S. M. (1980) Image and mind. Harvard University Press.Google Scholar
Levine, D. S. (2012) I think therefore I feel: Possible neural mechanisms for knowledge-based pleasure. In: Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 10–15, 2012, pp. 15. IEEE Press. doi: 10.1109/IJCNN.2012.6252413.Google Scholar
Masataka, N. & Perlovsky, L. I. (2012) The efficacy of musical emotions provoked by Mozart's music for the reconciliation of cognitive dissonance. Scientific Reports 2, Article number: 694. (Online publication). doi:10.1038/srep00694.CrossRefGoogle ScholarPubMed
Perlovsky, L. I. (1998) Conundrum of combinatorial complexity. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(6):666–70.CrossRefGoogle Scholar
Perlovsky, L. I. (2001) Neural networks and intellect: Using model-based concepts. Oxford University Press.Google Scholar
Perlovsky, L. I. (2006) Toward physics of the mind: Concepts, emotions, consciousness, and symbols. Physics of Life Reviews 3(1):2255.CrossRefGoogle Scholar
Perlovsky, L. I. (2007) Neural dynamic logic of consciousness: The knowledge instinct. In: Neurodynamics of higher-level cognition and consciousness, ed. Perlovsky, L. I. & Kozma, R., pp. 73108. Springer-Verlag.CrossRefGoogle Scholar
Perlovsky, L. I. (2009) “Vague-to-crisp” neural mechanism of perception. IEEE Transactions on Neural Networks 20(8):1363–67.CrossRefGoogle ScholarPubMed
Perlovsky, L. I. (2010a) Intersections of mathematical, cognitive, and aesthetic theories of mind. Psychology of Aesthetics, Creativity, and the Arts 4(1):1117. doi: 10.1037/a0018147.CrossRefGoogle Scholar
Perlovsky, L.I. (2010b) Musical emotions: Functions, origin, evolution. Physics of Life Reviews 7(1):227. doi:10.1016/j.plrev.2009.11.001.CrossRefGoogle ScholarPubMed
Perlovsky, L. I. (2012a) Cognitive function of music: Part I. Interdisciplinary Science Reviews 37(2):129–42.CrossRefGoogle Scholar
Perlovsky, L. I. (2012b) Cognitive function, origin, and evolution of musical emotions. Musicae Scientiae 16(2):185–99. doi: 10.1177/1029864912448327.CrossRefGoogle Scholar
Perlovsky, L. I. (2013a) A cognitive model of language and conscious processes. In: The unity of mind, brain and world, ed. Pereira, A. Jr. & Lehmann, D., pp. 265–68. Cambridge University Press.CrossRefGoogle Scholar
Perlovsky, L. I. (2013b) Language and cognition – joint acquisition, dual hierarchy, and emotional prosody. Frontiers in Behavioral Neuroscience 7, article 123. (Online journal). doi:10.3389/fnbeh.2013.00123.CrossRefGoogle ScholarPubMed
Perlovsky, L. I. (2013c) Learning in brain and machine – complexity, Gödel, Aristotle. Frontiers in Neurorobotics 7, article23. (Online journal). doi:10.3389/fnbot.2013.00023.CrossRefGoogle ScholarPubMed
Perlovsky, L. I. (2014a) Aesthetic emotions, what are their cognitive functions? Frontiers in Psychology 5, article 98. (Online journal) doi:10.3389/fpsyg.2014.00098. Available at: http://www.frontiersin.org/Journal/10.3389/fpsyg.2014.00098/full.CrossRefGoogle ScholarPubMed
Perlovsky, L. I. (2014b) The cognitive function of music: Part II. Interdisciplinary Science Reviews 39(2):162–86.CrossRefGoogle Scholar
Perlovsky, L. I. (2015) Origin of music and the embodied cognition. Frontiers in Psychology 6, article 538. (Online publication). Available at: http://dx.doi.org/10.3389/fpsyg.2015.00538.CrossRefGoogle ScholarPubMed
Perlovsky, L. I., Bonniot-Cabanac, M.-C. & Cabanac, M. (2010) Curiosity and pleasure. Webmed Central Psychology 1(12):WMC001275. Available at: http://www.webmedcentral.com/ article_view/1275Google Scholar
Perlovsky, L. I., Cabanac, A., Bonniot-Cabanac, M.-C. & Cabanac, M. (2013) Mozart effect, cognitive dissonance, and the pleasure of music. Behavioural Brain Research 244:914.CrossRefGoogle ScholarPubMed
Schoeller, F. (2015) The shivers of knowledge. Human and Social Studies 4(3):2641. ISSN (Online) , DOI: 10.1515/hssr-2015-0022, November 2015.CrossRefGoogle Scholar
Schoeller, F. & Perlovsky, L. (2015) Great expectations – Narratives and the elicitation of aesthetic chills. Psychology 6(16):2098–102; doi: 10.4236/psych.2015.616205. Available at: http://www.scirp.org/journal/psych CrossRefGoogle Scholar