Through a neuroeconomics lens of optimal foraging, expected utility, brain computation, and central aminergic reward systems, Shadmehr and Ahmed deconstruct classic decision-theory explanations for observed animal and human choice behavior in a badly needed effort to re-synthesize a more convincing adaptationist view of the origins, evolution, and nature of movement control. This root-source analysis leads the authors to justifiably reject outdated automaton traditions that champion the ill-reasoned partitioning of executive decision-making substrate and processes from those of all-or-none stereotypical action-making sequences. For Shadmehr and Ahmed, movement control relies on well integrated, if not entirely reciprocal, functional relationships between decision, motor, and modulator neurocircuits to determine subjective valuation of choice as embodied in modifiable fitness or utility, salience, and vigor of action to execute some goal-oriented plan. Vigor, proportional to the inverse function of time required to complete target-attaining motions, is a more-or-less recently accepted indirect measure of desire or demand in behavioral economics (Haith, Reppert, & Shadmehr, Reference Haith, Reppert and Shadmehr2012; Niv, Daw, Joel, & Dayan, Reference Niv, Daw, Joel and Dayan2007; Reppert, Lempert, Glimcher, & Shadmehr, Reference Reppert, Lempert, Glimcher and Shadmehr2015; Todorov & Jordan, Reference Todorov and Jordan2002; Yoon, Jaleel, Ahmed, & Shadmehr, Reference Yoon, Jaleel, Ahmed and Shadmehr2020). As a natural proclivity and empirical metric, vigor helps behaviorally contextualize motivation and target worth associated with nonlinear relative fitness or utility of past acquired and new forecasted outcomes, further implying motor control emerged from multilevel ecoevolutionary pressures driving rationality and affect across organism lifespans, generations, and phyla (cf. Clark, Reference Clark2018).
These broad assertions are narrowly and uniquely epitomized for the authors in one established mathematical framework – classic optimal foraging theory (Stephens & Krebs, Reference Stephens and Krebs1986). Optimal foraging theory derives from prospect and nonexpected utility theories (Bautista, Tinbergen, & Kacelnik, Reference Bautista, Tinbergen and Kacelnik2001; Kahneman & Tversky, Reference Kahneman and Tversky1979; Lemon, Reference Lemon1991; Stott, Reference Stott2006; Tversky & Kahneman, Reference Tversky and Kahneman1992), where utility or specific currency is quantified in global capture rates of optional goods, such as net energetic intake of niche-dispersed variable nutrition over time. Shadmehr and Ahmed use the theory to equate subjective purposefulness of utility with merits of cortical computation, cognitive effort, and weighted experience-dependent selection of movement energetics, precision, patterns or trajectories, magnitudes, latencies, and durations or periods to obtain reward. Optimal foraging theory improves upon the rigid absoluteness of standard utility theory and its psychological constructs of rational selfishness, objective value, and perfect or invariant agent choice of maximized final-state or one-trial utility under risk and uncertainty (Gollier, Reference Gollier2004; Von Neumann & Morgenstern, Reference Von Neumann and Morgenstern1953). Indeed, the theory accounts for both rationality and particular irrational cognitive biases, such as the Allais paradox, by introducing a value function taken from a relative or neutral gains-losses reference point (Kahneman & Tversky, Reference Kahneman and Tversky1979; Stott, Reference Stott2006), so (mis)perceived wealth variations may be affixed to expected utility to effect rule-of-thumb, strategy, or policy goodness appraisals governed by local and global parameters. When ecological tradeoffs favor local parameters, the marginal value theorem renders policies for nontrivial rational solutions, termed marginal or local returns, which maximize foraging success with spatiotemporal independence. That is, foragers prefer to pick best options with local capture rates backed by accurate knowledge of the status of current food availability and effort expenditures rather than running-average historical values distributed over time and space. Rational preferences at global capture rates may be determined by foragers when global parameters prevail in accurately giving best solutions, termed optimal or global returns, via spatiotemporally aggregate details. Decisions to stay or switch between these two extreme classes of foraging policies, and amounts of movement vigor exerted to minimize opportunity costs in procuring and consuming nutrients, depend on minimax equilibria or stability points between local and global returns in the universal utility probability density matrix or vector space and the thermodynamic-sensitive direction and magnitude of utility-symmetry breaking that produces suboptimal to optimal choice alternatives.
Classic decision theories based on classical probability theory, such as that formalizing popular Bayesian probability, often yield fair approximations of choice behavior and Shadmehr and Ahmed express their belief in the power, internal and external validity, and novel application of optimal foraging theory for better data-fitted descriptions of movement control. The authors, nonetheless, warn complexities in representing risk from subjective values of foraging reward, effort, and time limit the theory's predictive power, as do inconsistencies in estimating time spent collecting food from separate geographical patches or in wasting accessible abundant food sources. Although they attribute rational prediction failures to missing or poorly conceived model parameters, Shadmehr and Ahmed sadly neglect to address major experimentally identified paradoxes linked with stochastic error and other aspects of classic decision theories, damaging their attempt to create a foundational vigor-centered neuroeconomics interpretation of canonical decision and action making. Paradoxes that plaque classic decision theories, including disjunction and conjunction fallacies, Allais paradox, and Ellsberg or planning paradox (Allais, Reference Allais1953; Shafir & Tversky, Reference Shafir and Tversky1992; Tversky & Kahneman, Reference Tversky and Kahneman1983; Yukalov & Sornette, Reference Yukalov and Sornette2009), transfer to movement control (Clark & Hassert, Reference Clark and Hassert2013) and, therefore, violate classical probability axioms of normative movement-control risk and uncertainty within an optimal foraging approach. Gödelian completeness theorems (Reference Gödel1931; Clark & Hassert, Reference Clark and Hassert2013) importantly hinder possible development of any practical paradox-free complete and consistent classical neuroeconomics definition of movement control. Perhaps, the top neuroeconomics prescription for categorical and propositional logic paradoxes involves use of quantum cognition or decision theory, a mathematical method regrettably overlooked by Shadmehr and Ahmed. Quite successful in cognitive modeling, quantum decision theory is supported by quantum probability theory, a legitimate mathematics for formally assigning probabilities to events from quantum mechanics without physical constraints (Aerts, Reference Aerts2009; Aerts & Aerts, Reference Aerts and Aerts1995; Ashtiani & Azgomi, Reference Ashtiani and Azgomi2015; Beck, Reference Beck2016; Busemeyer & Bruza, Reference Busemeyer and Bruza2011; Busemeyer, Pothos, Franco, & Trueblood, Reference Busemeyer, Pothos, Franco and Trueblood2011; Chater, Reference Chater2015; Clark, Reference Clark and Salander2011, Reference Clark and Floares2012a, Reference Clark2012b, Reference Clark2014a, Reference Clark2014b, Reference Clark2015, Reference Clark2017, Reference Clark2020; Favre, Wittwer, Heinimann, Yukalov, & Sornette, Reference Favre, Wittwer, Heinimann, Yukalov and Sornette2016; Hu & Loo, Reference Hu and Loo2014; Pothos & Busemeyer, Reference Pothos and Busemeyer2013; Yukalov & Sornette, Reference Yukalov and Sornette2014). The axioms of quantum probability theory vary and might result in predictions that diverge, similar to the consequences of classical and relativistic probability axioms (Jumarie, Reference Jumarie1980, Reference Jumarie1984, Reference Jumarie1990; Nielson & Chuang, Reference Nielson and Chuang2000). However, they also provide necessary degrees of freedom – an infinite Hilbert space of known and hidden vectors representing cognitive-emotional-motor substrate, processes, states, and factors – to accommodate or correct many persistently troublesome pathologies common to prospect or nonexpected optimal foraging, including subjective bias inconsistencies which may irrationally affect accuracy of payoff, work, or time inferences and magnitude of corresponding movement vigor for individual and group decision makers (cf. Clark, Reference Clark2019; Pothos & Busemeyer, Reference Pothos and Busemeyer2009; Yukalov & Sornette, Reference Yukalov and Sornette2010).
Subjective bias inconsistencies in utility judgments are inherent in the complexities of risk representation and may manifest themselves as risk-order deliberation effects caused by conjunctive or disjunctive errors accompanying movement selection and execution, especially for unfamiliar and/or complex goal contexts. Shadmehr and Ahmed, as do other scientists, regard deliberation as a decision parameter bounded by classical probability density matrices that define distributions of rates for neurally integrating stimulus/reward traits and of latency thresholds for inducing behavioral performance. Theoretical models that employ variable rates with constant thresholds predict skewed reaction-time distributions, whereas models employing constant rates with variable thresholds predict normal reaction-time distributions, a poorer match to observed data on reaction time and vigor. Actual and forecasted reward and effort, which confer dissociable value to action utility, proportionately modulate vigor through the same sorts of deterministic and random variables and constants underlying movement deliberation, imbuing instantaneous (e.g., single reward-acquisition trial) or summated (e.g., serial reward-acquisition trials) utility with capacities to bias perception, memory, and deliberation during decision making. But classical probability theory notably cannot fully clarify psychological order effects, such as significant differential judgment values due only to order of perceived, recollected, and/or deliberated information, because all events are represented as probability submatrices of a respective universal matrix with commutative mathematical properties. For instance, the classical joint probability P(A ∩ B) ≠ 0 of event A, with probability submatrix PA = {p A1, …, p An}, intersecting event B, with probability submatrix PB = {p B1, …, p Bn}, is equivalent for ordered event pairs (A, B) and (B, A). Accordingly, if decision-action A, with risk probability submatrix PA to not receive payoffs (i.e., opportunity costs), and decision-action B, with risk probability submatrix PB to not receive payoffs (i.e., opportunity costs), intersect with joint probability P(A ∩ B) ≠ 0, then the joint risk probability or uncertainty of decisions-actions remains identical regardless of the ordered series of movement deliberations. Violation of the commutativity law for equally weighted risks and corresponding utilities and movement vigor for separate, probabilistically joint canonical decisions and actions constitutes a conjunctive error with irrational behavior unexplainable by classic optimal foraging theory. In contrast, quantum probability theory represents events as vectors or closed subspaces of Hilbert space, a universal vector space where conjunction of two such events or decisions-actions A and B may or may not exist (Atmanspacher & Römer, Reference Atmanspacher and Römer2012; Wang & Busemeyer, Reference Wang and Busemeyer2015). Conjunction between events or decisions-actions is absent when events or decisions-actions are noncommutative and complementary or mutually exclusive, allowing for random or nonrandom order effects to influence definite deliberation by foragers unable to perform simultaneous or compatible perceptual, attentional, emotive, motivational, pneumonic, and decisional assessments, among other psychological processes necessary for rational motor control.
Conjunctive errors and resultant irrational decision-action risk evaluations resemble other risk-order superstitious behaviors, including the Gambler's Fallacy, where learned increases in behavior frequency, such as riding-out strings of statistically independent losing choices in hope of turning bad luck into prosperity, are caused by accidental or random pairings of reinforcement with behavior and by an inability to logically perceive, calculate, assign, and/or understand real outcome probabilities. Each type of choice bias may become evident when foraging scenarios force actual local and global returns into equilibrium, whether or not both returns are suboptimal, near optimal, or optimal. At equilibrium, a forager earns the same utility at the same elemental and same joint probabilities, despite possible intermittent or continued use of a (naturally or artificially elicited) favorite order policy distinguishing subjective bias and irrationality (i.e., local-before-global vs. global-before-local returns selection). Irrational order effects may be explained with standard learning and cognitive (computation) theory, such as primacy and recency effects due to resource-allocation limitations, priming, or higher-order instrumental learning. Quantum decision theory agrees with classic decision theories on this matter. Quantum decision theory takes a black-box approach, sometimes called cognitive completeness (Tressoldi, Maier, Buechner, & Khrennikov, Reference Tressoldi, Maier, Buechner and Khrennikov2015; Yearsley & Pothos, Reference Yearsley and Pothos2014), which isolates any evaluated cognitive system from the formidable measurement problem of quantum mechanics and information theory. Scientists believe the scalable neurophysiological contents of this black box map onto cognitive states relevant to particular sets of judgments and their corresponding outcome probabilities. Such theoretical elegance in describing complex choice behavior pushes quantum aspects of brain structure and function beyond most current modeling endeavors, although defining computational features of brain areas, cells, and macromolecules, such as those noted by Shadmehr and Ahmed, may be tractable under certain conditions. Evidence from decades of analytical and experimental research continues to oppose the conventional tenet that quantum mechanical phenomena exert, at most, trivial influences over bioprocesses (Davies, Reference Davies2004). Criticisms still concentrate on the likelihood of biological systems cohering into a quantum regime long enough to accomplish quantum computation. However, issues regarding quantum decoherence, the collapse of the Schrödinger wave function into a single classical or macroscopic state because of thermodynamic processes involving a system and its environment, are less problematic for cellular enzymatic processes reliant on small, thermally-shielded protein reaction sites and/or on local temperature gradients which drive cellular substrate from decoherent to coherent activity.
Considering these points, substrates essential for neuronal computations are connected with quantum operation characteristics, such as cytoskeletal lattices, the citric acid cycle and metabolism, molecule folding, synaptic boutons and vesicles, and autocatalytic second-messenger cascades (Clark, Reference Clark2012b, Reference Clark2015, Reference Clark2017). Quantum effects at both informational and physical degrees of freedom thus seem to appear at every key level of brain structure and function, with activity maintaining capacities to benefit signal coincidence detection and integration, bidirectional synaptic plasticity, and other vital cell functions by rapidly selecting, ordering, and/or counting optional cellular processes (Clark, Reference Clark2014b). Scaling quantum effects between microscopic and macroscopic physical states, such as that associated with entire brains and probabilistic cognitive events, including perception, recollection, and deliberation, fills the black box of cognitive completeness and affirms a quantum neuroeconomics of rational and irrational movement control and goal attainment.
Through a neuroeconomics lens of optimal foraging, expected utility, brain computation, and central aminergic reward systems, Shadmehr and Ahmed deconstruct classic decision-theory explanations for observed animal and human choice behavior in a badly needed effort to re-synthesize a more convincing adaptationist view of the origins, evolution, and nature of movement control. This root-source analysis leads the authors to justifiably reject outdated automaton traditions that champion the ill-reasoned partitioning of executive decision-making substrate and processes from those of all-or-none stereotypical action-making sequences. For Shadmehr and Ahmed, movement control relies on well integrated, if not entirely reciprocal, functional relationships between decision, motor, and modulator neurocircuits to determine subjective valuation of choice as embodied in modifiable fitness or utility, salience, and vigor of action to execute some goal-oriented plan. Vigor, proportional to the inverse function of time required to complete target-attaining motions, is a more-or-less recently accepted indirect measure of desire or demand in behavioral economics (Haith, Reppert, & Shadmehr, Reference Haith, Reppert and Shadmehr2012; Niv, Daw, Joel, & Dayan, Reference Niv, Daw, Joel and Dayan2007; Reppert, Lempert, Glimcher, & Shadmehr, Reference Reppert, Lempert, Glimcher and Shadmehr2015; Todorov & Jordan, Reference Todorov and Jordan2002; Yoon, Jaleel, Ahmed, & Shadmehr, Reference Yoon, Jaleel, Ahmed and Shadmehr2020). As a natural proclivity and empirical metric, vigor helps behaviorally contextualize motivation and target worth associated with nonlinear relative fitness or utility of past acquired and new forecasted outcomes, further implying motor control emerged from multilevel ecoevolutionary pressures driving rationality and affect across organism lifespans, generations, and phyla (cf. Clark, Reference Clark2018).
These broad assertions are narrowly and uniquely epitomized for the authors in one established mathematical framework – classic optimal foraging theory (Stephens & Krebs, Reference Stephens and Krebs1986). Optimal foraging theory derives from prospect and nonexpected utility theories (Bautista, Tinbergen, & Kacelnik, Reference Bautista, Tinbergen and Kacelnik2001; Kahneman & Tversky, Reference Kahneman and Tversky1979; Lemon, Reference Lemon1991; Stott, Reference Stott2006; Tversky & Kahneman, Reference Tversky and Kahneman1992), where utility or specific currency is quantified in global capture rates of optional goods, such as net energetic intake of niche-dispersed variable nutrition over time. Shadmehr and Ahmed use the theory to equate subjective purposefulness of utility with merits of cortical computation, cognitive effort, and weighted experience-dependent selection of movement energetics, precision, patterns or trajectories, magnitudes, latencies, and durations or periods to obtain reward. Optimal foraging theory improves upon the rigid absoluteness of standard utility theory and its psychological constructs of rational selfishness, objective value, and perfect or invariant agent choice of maximized final-state or one-trial utility under risk and uncertainty (Gollier, Reference Gollier2004; Von Neumann & Morgenstern, Reference Von Neumann and Morgenstern1953). Indeed, the theory accounts for both rationality and particular irrational cognitive biases, such as the Allais paradox, by introducing a value function taken from a relative or neutral gains-losses reference point (Kahneman & Tversky, Reference Kahneman and Tversky1979; Stott, Reference Stott2006), so (mis)perceived wealth variations may be affixed to expected utility to effect rule-of-thumb, strategy, or policy goodness appraisals governed by local and global parameters. When ecological tradeoffs favor local parameters, the marginal value theorem renders policies for nontrivial rational solutions, termed marginal or local returns, which maximize foraging success with spatiotemporal independence. That is, foragers prefer to pick best options with local capture rates backed by accurate knowledge of the status of current food availability and effort expenditures rather than running-average historical values distributed over time and space. Rational preferences at global capture rates may be determined by foragers when global parameters prevail in accurately giving best solutions, termed optimal or global returns, via spatiotemporally aggregate details. Decisions to stay or switch between these two extreme classes of foraging policies, and amounts of movement vigor exerted to minimize opportunity costs in procuring and consuming nutrients, depend on minimax equilibria or stability points between local and global returns in the universal utility probability density matrix or vector space and the thermodynamic-sensitive direction and magnitude of utility-symmetry breaking that produces suboptimal to optimal choice alternatives.
Classic decision theories based on classical probability theory, such as that formalizing popular Bayesian probability, often yield fair approximations of choice behavior and Shadmehr and Ahmed express their belief in the power, internal and external validity, and novel application of optimal foraging theory for better data-fitted descriptions of movement control. The authors, nonetheless, warn complexities in representing risk from subjective values of foraging reward, effort, and time limit the theory's predictive power, as do inconsistencies in estimating time spent collecting food from separate geographical patches or in wasting accessible abundant food sources. Although they attribute rational prediction failures to missing or poorly conceived model parameters, Shadmehr and Ahmed sadly neglect to address major experimentally identified paradoxes linked with stochastic error and other aspects of classic decision theories, damaging their attempt to create a foundational vigor-centered neuroeconomics interpretation of canonical decision and action making. Paradoxes that plaque classic decision theories, including disjunction and conjunction fallacies, Allais paradox, and Ellsberg or planning paradox (Allais, Reference Allais1953; Shafir & Tversky, Reference Shafir and Tversky1992; Tversky & Kahneman, Reference Tversky and Kahneman1983; Yukalov & Sornette, Reference Yukalov and Sornette2009), transfer to movement control (Clark & Hassert, Reference Clark and Hassert2013) and, therefore, violate classical probability axioms of normative movement-control risk and uncertainty within an optimal foraging approach. Gödelian completeness theorems (Reference Gödel1931; Clark & Hassert, Reference Clark and Hassert2013) importantly hinder possible development of any practical paradox-free complete and consistent classical neuroeconomics definition of movement control. Perhaps, the top neuroeconomics prescription for categorical and propositional logic paradoxes involves use of quantum cognition or decision theory, a mathematical method regrettably overlooked by Shadmehr and Ahmed. Quite successful in cognitive modeling, quantum decision theory is supported by quantum probability theory, a legitimate mathematics for formally assigning probabilities to events from quantum mechanics without physical constraints (Aerts, Reference Aerts2009; Aerts & Aerts, Reference Aerts and Aerts1995; Ashtiani & Azgomi, Reference Ashtiani and Azgomi2015; Beck, Reference Beck2016; Busemeyer & Bruza, Reference Busemeyer and Bruza2011; Busemeyer, Pothos, Franco, & Trueblood, Reference Busemeyer, Pothos, Franco and Trueblood2011; Chater, Reference Chater2015; Clark, Reference Clark and Salander2011, Reference Clark and Floares2012a, Reference Clark2012b, Reference Clark2014a, Reference Clark2014b, Reference Clark2015, Reference Clark2017, Reference Clark2020; Favre, Wittwer, Heinimann, Yukalov, & Sornette, Reference Favre, Wittwer, Heinimann, Yukalov and Sornette2016; Hu & Loo, Reference Hu and Loo2014; Pothos & Busemeyer, Reference Pothos and Busemeyer2013; Yukalov & Sornette, Reference Yukalov and Sornette2014). The axioms of quantum probability theory vary and might result in predictions that diverge, similar to the consequences of classical and relativistic probability axioms (Jumarie, Reference Jumarie1980, Reference Jumarie1984, Reference Jumarie1990; Nielson & Chuang, Reference Nielson and Chuang2000). However, they also provide necessary degrees of freedom – an infinite Hilbert space of known and hidden vectors representing cognitive-emotional-motor substrate, processes, states, and factors – to accommodate or correct many persistently troublesome pathologies common to prospect or nonexpected optimal foraging, including subjective bias inconsistencies which may irrationally affect accuracy of payoff, work, or time inferences and magnitude of corresponding movement vigor for individual and group decision makers (cf. Clark, Reference Clark2019; Pothos & Busemeyer, Reference Pothos and Busemeyer2009; Yukalov & Sornette, Reference Yukalov and Sornette2010).
Subjective bias inconsistencies in utility judgments are inherent in the complexities of risk representation and may manifest themselves as risk-order deliberation effects caused by conjunctive or disjunctive errors accompanying movement selection and execution, especially for unfamiliar and/or complex goal contexts. Shadmehr and Ahmed, as do other scientists, regard deliberation as a decision parameter bounded by classical probability density matrices that define distributions of rates for neurally integrating stimulus/reward traits and of latency thresholds for inducing behavioral performance. Theoretical models that employ variable rates with constant thresholds predict skewed reaction-time distributions, whereas models employing constant rates with variable thresholds predict normal reaction-time distributions, a poorer match to observed data on reaction time and vigor. Actual and forecasted reward and effort, which confer dissociable value to action utility, proportionately modulate vigor through the same sorts of deterministic and random variables and constants underlying movement deliberation, imbuing instantaneous (e.g., single reward-acquisition trial) or summated (e.g., serial reward-acquisition trials) utility with capacities to bias perception, memory, and deliberation during decision making. But classical probability theory notably cannot fully clarify psychological order effects, such as significant differential judgment values due only to order of perceived, recollected, and/or deliberated information, because all events are represented as probability submatrices of a respective universal matrix with commutative mathematical properties. For instance, the classical joint probability P(A ∩ B) ≠ 0 of event A, with probability submatrix PA = {p A1, …, p An}, intersecting event B, with probability submatrix PB = {p B1, …, p Bn}, is equivalent for ordered event pairs (A, B) and (B, A). Accordingly, if decision-action A, with risk probability submatrix PA to not receive payoffs (i.e., opportunity costs), and decision-action B, with risk probability submatrix PB to not receive payoffs (i.e., opportunity costs), intersect with joint probability P(A ∩ B) ≠ 0, then the joint risk probability or uncertainty of decisions-actions remains identical regardless of the ordered series of movement deliberations. Violation of the commutativity law for equally weighted risks and corresponding utilities and movement vigor for separate, probabilistically joint canonical decisions and actions constitutes a conjunctive error with irrational behavior unexplainable by classic optimal foraging theory. In contrast, quantum probability theory represents events as vectors or closed subspaces of Hilbert space, a universal vector space where conjunction of two such events or decisions-actions A and B may or may not exist (Atmanspacher & Römer, Reference Atmanspacher and Römer2012; Wang & Busemeyer, Reference Wang and Busemeyer2015). Conjunction between events or decisions-actions is absent when events or decisions-actions are noncommutative and complementary or mutually exclusive, allowing for random or nonrandom order effects to influence definite deliberation by foragers unable to perform simultaneous or compatible perceptual, attentional, emotive, motivational, pneumonic, and decisional assessments, among other psychological processes necessary for rational motor control.
Conjunctive errors and resultant irrational decision-action risk evaluations resemble other risk-order superstitious behaviors, including the Gambler's Fallacy, where learned increases in behavior frequency, such as riding-out strings of statistically independent losing choices in hope of turning bad luck into prosperity, are caused by accidental or random pairings of reinforcement with behavior and by an inability to logically perceive, calculate, assign, and/or understand real outcome probabilities. Each type of choice bias may become evident when foraging scenarios force actual local and global returns into equilibrium, whether or not both returns are suboptimal, near optimal, or optimal. At equilibrium, a forager earns the same utility at the same elemental and same joint probabilities, despite possible intermittent or continued use of a (naturally or artificially elicited) favorite order policy distinguishing subjective bias and irrationality (i.e., local-before-global vs. global-before-local returns selection). Irrational order effects may be explained with standard learning and cognitive (computation) theory, such as primacy and recency effects due to resource-allocation limitations, priming, or higher-order instrumental learning. Quantum decision theory agrees with classic decision theories on this matter. Quantum decision theory takes a black-box approach, sometimes called cognitive completeness (Tressoldi, Maier, Buechner, & Khrennikov, Reference Tressoldi, Maier, Buechner and Khrennikov2015; Yearsley & Pothos, Reference Yearsley and Pothos2014), which isolates any evaluated cognitive system from the formidable measurement problem of quantum mechanics and information theory. Scientists believe the scalable neurophysiological contents of this black box map onto cognitive states relevant to particular sets of judgments and their corresponding outcome probabilities. Such theoretical elegance in describing complex choice behavior pushes quantum aspects of brain structure and function beyond most current modeling endeavors, although defining computational features of brain areas, cells, and macromolecules, such as those noted by Shadmehr and Ahmed, may be tractable under certain conditions. Evidence from decades of analytical and experimental research continues to oppose the conventional tenet that quantum mechanical phenomena exert, at most, trivial influences over bioprocesses (Davies, Reference Davies2004). Criticisms still concentrate on the likelihood of biological systems cohering into a quantum regime long enough to accomplish quantum computation. However, issues regarding quantum decoherence, the collapse of the Schrödinger wave function into a single classical or macroscopic state because of thermodynamic processes involving a system and its environment, are less problematic for cellular enzymatic processes reliant on small, thermally-shielded protein reaction sites and/or on local temperature gradients which drive cellular substrate from decoherent to coherent activity.
Considering these points, substrates essential for neuronal computations are connected with quantum operation characteristics, such as cytoskeletal lattices, the citric acid cycle and metabolism, molecule folding, synaptic boutons and vesicles, and autocatalytic second-messenger cascades (Clark, Reference Clark2012b, Reference Clark2015, Reference Clark2017). Quantum effects at both informational and physical degrees of freedom thus seem to appear at every key level of brain structure and function, with activity maintaining capacities to benefit signal coincidence detection and integration, bidirectional synaptic plasticity, and other vital cell functions by rapidly selecting, ordering, and/or counting optional cellular processes (Clark, Reference Clark2014b). Scaling quantum effects between microscopic and macroscopic physical states, such as that associated with entire brains and probabilistic cognitive events, including perception, recollection, and deliberation, fills the black box of cognitive completeness and affirms a quantum neuroeconomics of rational and irrational movement control and goal attainment.
Conflict of interest
None.