Simplifying heuristics versus careful thinking: Scientific analysis of millennial spiritual issues

There is ample evidence that humans (and other pri- mates) possess a knowledge instinct—a biologically driven impulse to make coherent sense of the world at the highest level possible. Yet behavioral decision-making data suggest a contrary biological drive to minimize cognitive effort by solving problems using simplifying heuristics. Individuals differ, and the same person varies over time, in the strength of the knowledge instinct. Neuroimaging studies sug- gest which brain regions might mediate the balance between knowl- edge expansion and heuristic simplification. One region implicated in primary emotional experience is more activated in individuals who use primitive heuristics, whereas two areas of the cortex are more activated in individuals with a strong knowledge drive: one region implicated in detecting risk or conflict and another implicated in generating creative ideas. Knowledge maximization and effort mini- mization are both evolutionary adaptations, and both are valuable in different contexts. Effort minimization helps us make minor and rou- tine decisions efficiently, whereas knowledge maximization connects us to the beautiful, to the sublime, and to our highest aspirations. We relate the opposition between the knowledge instinct and heuristics to the biblical story of the fall, and argue that the causal scientific worldview is mathematically equivalent to teleological arguments from final causes. Elements of a scientific program are formulated to ad- dress unresolved issues.

[1]  Leonid I. Perlovsky,et al.  Neural Dynamic Logic of Consciousness: the Knowledge Instinct , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[2]  M. Botvinick,et al.  Conflict monitoring and cognitive control. , 2001, Psychological review.

[3]  Wesley R. Elsberry,et al.  Optimality in Biological and Artificial Networks , 1997 .

[4]  R. Shiffrin,et al.  Controlled and automatic human information processing: I , 1977 .

[5]  L. Perlovsky Toward physics of the mind: Concepts, emotions, consciousness, and symbols , 2006 .

[6]  Karl H. Pribram,et al.  Psychophysiology of the frontal lobes , 1973 .

[7]  Daeyeol Lee,et al.  Neurobiology of decision making , 2006, Neural Networks.

[8]  G. Schoenbaum,et al.  Encoding Predicted Outcome and Acquired Value in Orbitofrontal Cortex during Cue Sampling Depends upon Input from Basolateral Amygdala , 2003, Neuron.

[9]  R. Penrose,et al.  Shadows of the Mind , 1994 .

[10]  J. Cacioppo,et al.  DISPOSITIONAL DIFFERENCES IN COGNITIVE MOTIVATION : THE LIFE AND TIMES OF INDIVIDUALS VARYING IN NEED FOR COGNITION , 1996 .

[11]  E. F. Schumacher,et al.  A Guide for the Perplexed , 1977 .

[12]  S. Grossberg The Link between Brain Learning, Attention, and Consciousness , 1999, Consciousness and Cognition.

[13]  Leonid Perlovsky Modeling Field Theory of Higher Cognitive Functions , 2007 .

[14]  Ola Svenson,et al.  On decision rules and information processing strategies for choices among multiattribute alternatives , 1976 .

[15]  Linda Simon,et al.  Evidence That the Production of Aversive Consequences Is Not Necessary to Create Cognitive Dissonance , 1996 .

[16]  Moses Maimonides,et al.  A Guide for the Perplexed , 1954 .

[17]  D. Levine Neural network modeling of emotion , 2007 .

[18]  R. Lewontin ‘The Selfish Gene’ , 1977, Nature.

[19]  S. Grossberg,et al.  Neural dynamics of attentionally modulated Pavlovian conditioning: blocking, interstimulus interval, and secondary reinforcement. , 1987, Applied optics.

[20]  Joshua W. Brown,et al.  Learned Predictions of Error Likelihood in the Anterior Cingulate Cortex , 2005, Science.

[21]  Michael Barr,et al.  The Emperor's New Mind , 1989 .

[22]  S. Grossberg,et al.  Neural dynamics of attentionally modulated Pavlovian conditioning: Conditioned reinforcement, inhibition, and opponent processing , 1987, Psychobiology.

[23]  J. Cacioppo,et al.  The need for cognition. , 1982 .

[24]  N. Yeung,et al.  Anterior Cingulate Cortex , 2002 .

[25]  John W. Payne,et al.  The adaptive decision maker: Name index , 1993 .

[26]  D. Kumaran,et al.  Frames, Biases, and Rational Decision-Making in the Human Brain , 2006, Science.

[27]  D.S. Levine,et al.  Modeling emotional influences on human decision making under risk , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[28]  C. Keyes The triune brain in evolution: Role in paleocerebral functions: By Paul D. MacLean. New York: Plenum, 1990, xxiv + 672 pp , 1991 .

[29]  S. Grossberg Neural Networks and Natural Intelligence , 1988 .

[30]  F. Nietzsche Thus Spake Zarathustra , 2019 .

[31]  Robert P. Abelson,et al.  Modes of resolution of belief dilemmas , 1959 .

[32]  S. Pinker The language instinct : how the mind creates language , 1995 .

[33]  A. Tversky,et al.  Judgment under Uncertainty , 1982 .

[34]  Huston Smith,et al.  The Religions of Man , 1959 .

[35]  H F HARLOW,et al.  Mice, monkeys, men, and motives. , 1953, Psychological review.

[36]  Daniel S. Levine,et al.  Multiattribute Decision Making in Context: A Dynamic Neural Network Methodology , 1996 .

[37]  Eric J. Johnson,et al.  The adaptive decision maker , 1993 .

[38]  Stephen Grossberg,et al.  A massively parallel architecture for a self-organizing neural pattern recognition machine , 1988, Comput. Vis. Graph. Image Process..

[39]  S. Zeki A vision of the brain , 1993 .

[40]  Daniel S. Levine,et al.  How Does the Brain Create, Change, and Selectively Override its Rules of Conduct? , 2007 .

[41]  E. Harmon-Jones,et al.  Cognitive dissonance: Progress on a pivotal theory in social psychology. , 1999 .

[42]  Seymour Epstein,et al.  The interaction of three facets of concrete thinking in a game of chance , 1999 .

[43]  R. Shepard,et al.  Psychologically simple motions as geodesic paths. part I. Asymmetric objects , 1990 .

[44]  S. Vaisrub,et al.  A guide for the perplexed. , 1966, Manitoba medical review.

[45]  Leonid Perlovsky,et al.  Neural Networks and Intellect: Using Model-Based Concepts , 2000, IEEE Transactions on Neural Networks.

[46]  L. Festinger,et al.  A Theory of Cognitive Dissonance , 2017 .

[47]  J. Cacioppo,et al.  DISPOSITIONAL DIFFERENCES IN COGNITIVE MOTIVATION : THE LIFE AND TIMES OF INDIVIDUALS VARYING IN NEED FOR COGNITION , 1996 .

[48]  Stephen Grossberg,et al.  How laminar frontal cortex and basal ganglia circuits interact to control planned and reactive saccades , 2004, Neural Networks.

[49]  I. THE ATTENTION SYSTEM OF THE HUMAN BRAIN , 2002 .

[50]  Daniel S. Levine,et al.  Neural Network Modeling , 2002 .

[51]  Daniel Kahneman,et al.  The Framing of Decisions and the Rationality of Choice. , 1980 .

[52]  T. Robbins,et al.  Dissociation in prefrontal cortex of affective and attentional shifts , 1996, Nature.

[53]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[54]  M. Posner Attention in cognitive neuroscience: An overview. , 1995 .

[55]  Daniel S. Levine,et al.  Emotion and Decision Making: Short-term Reactions versus Long-term Evaluations , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[56]  Leonid I. Perlovsky,et al.  Maximum likelihood neural networks for sensor fusion and adaptive classification , 1991, Neural Networks.

[57]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[58]  A. Pavlovic,et al.  The anterior cingulate cortex , 2009 .

[59]  G. McCarthy,et al.  Dissociable prefrontal brain systems for attention and emotion , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[60]  Paul D. MacLean,et al.  An Explanation of Behavior. (Book Reviews: The Triune Brain in Evolution. Role in Paleocerebral Functions.) , 1990 .

[61]  R. Feynman,et al.  Quantum Mechanics and Path Integrals , 1965 .

[62]  Stephen Grossberg,et al.  ART 3: Hierarchical search using chemical transmitters in self-organizing pattern recognition architectures , 1990, Neural Networks.

[63]  A. Damasio Descartes' error: emotion, reason, and the human brain. avon books , 1994 .

[64]  Leonid I. Perlovsky,et al.  Neural Networks, Fuzzy Models and Dynamic Logic , 2007, Aspects of Automatic Text Analysis.

[65]  M. R. Leippe,et al.  Physiological arousal, dissonance, and attitude change: evidence for a dissonance-arousal link and a "don't remind me" effect. , 1986, Journal of personality and social psychology.

[66]  Daniel S. Levine,et al.  A neural network theory of proportional analogy-making , 2000, Neural Networks.