vanguard project - part 1: a neuroeconomic theory
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Running Head: The Minds Eye
The Minds Eye
Chris Frueh
Rutgers University
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Abstract
The Purpose of this paper is to trace the process of situation-pattern-recognition
through the various function-modules of the brain in order to define a subconscious
neural framework for the problem-solving-by-analogy theory. I will present an
experimental procedure to highlight, via functional imagery, the subconscious pattern
recognition and resolution response to the brief exposure of a complex problem state. In
the second part of the paper, I will elaborate a framework to explain the possible results
in light of an expected utility function married to a computer-housed virtual recognition
protocol. This, I will fold this system into a model for a goal-oriented, intuition-
replicating artificial intelligence. To conclude, I will highlight future research possibilities
to further confirm or concretely refute the framework foundational to this paper, that of
the module theory of brain activity.
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Introduction
The branch of problem solving confronted herein is loosely defined as complex
problem solving by analogy requiring goal-oriented decision-making based on the brief
exposure to the subject of the situational characteristics and requiring a rapid response
informed by recollection of previously encountered scenarios of some similarity.
Problem Solving Through Hypotheticals
(Politser 14)
The above illustration details the traditional view of how a problem states
resolution is attained, namely through the mental projection of hypothetical outcomes and
the analysis thereof. I, however, would like to tweak this model somewhat as it is far too
slow (relying on System 2 type of rational thought) and is vague on the influence of
memory. Instead, I would postulate that the node marked Perception is the priming
effect that readies the access to similar scenarios (Kahnemann, 2003, p 452-3), that the
entire Hypothetical loop terminating in the actual decision is encapsulated in the
subconscious memory of previously successful action-outcome pairs and that the
successful analogy from the current to the remembered is a brief System 2 intrusion (at
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the Diagnosis node) into an exclusively System 1 task. This model would account for the
rapid-response type of intuition exhibited during a mutating ambiguous problem state
over an unbounded spatial area.
The second area that requires introduction is the field of neuroeconomics.
(Politser, 2007, p. 32) Put briefly, neuroeconomics is a neuroscientists examination of the
brain during economic activities. The particular application to this problem is an attempt
to rework the model of analogy-driven problem solving through the use of neural
imaging and optimization (similar to Bayesian inference). Within the experiment below,
the skeletal form of an expected utility function is the outline I assume, for the sake of
argument, the subject follows.
Experimental Procedure
The structure of the experiment will be the focused on the neurological response
to a brief exposure of a complex problem state during the subjects formulation of a
response to the problem. In particular, I will flash an image of a chessboard with the
pieces set up in a variation of the Sicilian Defense (or the Winawer variation of the
French defense) known as the Poisoned Pawn. The reason this particular problem was
chosen was because of the possibility of a favorable solution for either an aggressive1 or a
defensive response.2 The subject(s) will be one or more experienced chess players. This
condition is necessary to prevent the pattern recognition function to be engaged by a
novice player recognizing the pieces themselves instead of the pattern of placement.
1 http://www.chessgames.com/perl/chessgame?gid=10447282 http://www.chessgames.com/perl/chessgame?gid=1044724
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The Poisoned Pawn Variation of the Sicilian Defense
This experiment will take two parts. After establishing a baseline for the subjects
brain at rest, I will expose him or her to one of the two variations of the gambit while he
is attached to an fMRI. The readings will begin upon exposure of the stimulus and will
end when he or she verbalizes a response to the situation (i.e. aggress or retreat) This will,
in effect, calibrate the later readings to the particular layout of the subjects brain patterns
but without the time-sensitive readings that allow for a correlative hypothesis about the
path of the information. I will record the areas that showed above average blood flow
and, under the assumption that these areas played a role in the pattern recognition, will
focus a second repetition using more time-sensitive equipment in order to support this
assumption and the overall hypothesis.
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In the second part, I will repeat the previous protocols but with the subject
attached to an EEG machine instead of an fMRI and using the gambit variation that was
not used in the first part in order to keep the recognition based on playing experience
rather than short-term memory. Again, the recording will begin at exposure and end at
verbalization but, in interpreting the neural activity results, the response will be presumed
to have been given upon activation of the speech centers of the brain. This, I believe,
would provide a more concise time frame for the exercise.
The recorded results will be, simply, where activation occurred during both
exposures and when it occurred as measured during the second exposure. I expect initial
firings to be in the occipital cortex as the subject views the situation. From there, I expect
information to be sent to the parietal cortex as the various visual-spatial coordinates of
the pieces are catalogued. Next, I expect firings to occur in the temporal lobe as the
similarity of the situation acts like a priming stimulus to bring to mind the previously
encountered scenarios from the subjects experience. This should be rapid and
subconscious, fitting with Kahnemanns (2003) placement of similarity firmly within the
bounds of System 1 thought processes. (p. 453) As the situation is recalled, I expect
activity in the anterior cingulate cortex as goals are analyzed in relation to previous
problem states. Simultaneously, there may also be activity in the various portions of the
brain that evaluate hypothetical outcomes (comparing the hypothetical outcomes with
previously encountered outcomes) such as the ventromedial prefrontal cortex which has
strong ties to predictive utility. This pattern comparison is also subconscious as postulated
by Rosenblatt and Thickstun. (Rosenblatt, 1993, pg. 700) As this problem solving
function begins to move towards production of a response, I expect significant activity in
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the orbitofrontal cortex or the amygdala as the subject weighs the salience of uncertainty
or ambiguity. While the effect of risk aversion will not alter the hypothesis, it is important
to note the role of the neural structures that house the risk-aversion functions and the
time-specific point of their impact on the decision-making process. Lastly, I expect the
firings to converge on the frontal cortexs executive decision center before a response is
vocalized.
Conclusion
While the primary benefit of this experiment would be confirmation or denial of
the theory of brain function localization, a significant secondary benefit would be a
framework on which cognition-mimicking software might be based. For example, pattern
comparison and organization is a task computers have been handling since the turn of the
century, but, if this framework is valid, AI programmers might adapt these sorts of
functions for use in a pattern-recognition-based machine capable of learning from
previous scenarios (as the visual-spatial coordinates that the parietal cortex analyzes are
written into the memory as a new situation able to be remembered). The priming effect
would be simulated by a pattern comparison formula and the analogy-inferring process
might be replicated by an organization or optimization formula. This, however, is
contingent upon the modular theory of brain functionality and, more inhibiting, a coding
structure capable of self-referential or self-modifying coding.
Further research that might be done to examine the possibility of the theories
hypothesized herein might be done by dissecting brain matter. Following in the footsteps
of Wernicke, if the recognition function is localized to these specific brain structures,
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there will probably be bundles of neurons between these areas similar to the path
between Wernickes and Brocas areas. (Cognition, Brain, and Consciousness, 2007, pg,
6) This could expand the ability of neuropathologists to understand brain damage: if
damage is not localized to a specific structure but, rather, is between two structures, one
might draw conclusions about the role of the previously connected structures from the
symptoms in evidence after the damage.
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Works Cited
Chen, S. (2008, November). Software-Agent Designs in Economics: An Interdisciplinary
Framework.IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 18-22.
Foxall, G. R. (2008). Reward, emotion and consumer choice: from neuroeconomics to
neurophilosophy.Journal of Consumer Behaviour, 7, 368-396.
Gill, T. G. (2008). A Psychologically Plausible Goal-Based Utility Function.Informing
Science: the International Journal of an Emerging Transdiscipline, 11, 227-252.
Kahneman, D. (2003). A perspective on judgment and choice: mapping bounded
rationality..Am Psychol, 58(9), 697-720.
Politser, P. (2007).Neurorationality: A Neuroeconomic Approach to Mental Health and
Good Sense. New York: Oxford University Press, USA.
Rosenblatt, A., & Thickstun, T. (1993). Intuition and Consciousness.Psychoanalytic
Quarterly, 63, 696-714.
Rustichini, A. (2008). Dual or unitary system? Two alternative models of decision
making. Cognitive, Affective, & Behavioral Neuroscience, 8(4), 355-362.
(2007). Cognition, Brain, and Consciousness: Introduction to Cognitive Neuroscience.
Toronto: Academic Press.
(1995). Complex Problem Solving: The European Perspective. Mahwah, NJ: Lawrence
Erlbaum.
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