Some Paradoxical Issues in Neuromanagement of Decision - Making

Topics: Decision making, Brain, Cognition Pages: 34 (11084 words) Published: May 22, 2012

Jyotirmaya S.
D. Litt. Candidate

--------------------------------------------------------------------------------------- PROLOGUE
New brain imaging technologies have motivated neuromanagement studies of the internal order of the mind and its links with the spectrum of human decisions from choice among fixed gambles to choice mediated by market and other institutional rules. We are only at the beginning of the enterprise, but its promise suggests a fundamental change in how we think, observe and model decision in all its contexts.

…….. Vernon Smith
Nobel Laureate (Managements, 2002) Everyday life is full of decisions and choices. An important question for many researchers is how people make (management) decisions. Specifically, researchers are interested in the assumptions, beliefs, habits, and tactics that people use to make everyday decisions. Research suggests that the brain considers various sources of information before making a decision. However, how does it do this? In addition, why does the process sometimes go awry, causing us to make impulsive, indecisive, and confused decisions; the kinds that can lead to risky and potentially dangerous behaviours? Human behaviour is not the product of a single process, but rather reflects the interaction of different specialized subsystems. These systems, the idea goes, usually interact seamlessly to determine behaviour, but at times, they compete. Result is that brain sometimes argues with itself, as these distinct systems come to different conclusions about what we should do. Human behaviour, in general, is not under constant and detailed control of careful and accurate hedonic calculations, but is product of an unstable and irrational complex of reflex actions, impulses, instincts, habits, customs, fashion, and hysteria. For a long time, economists have argued that humans make decisions by obeying laws of rationality. Decisions are an inevitable part of human activities. Quantification of choice has been a major area of research for behavioural scientists for several decades. This is, in part, due to the discovery of the ‘Matching Law’ that stipulates that relative response rate on concurrently available alternatives ‘match’ the available relative reinforcement rates. This theoretical construct has been developed to describe response allocation in more complex situations. People often fail to design ‘rational’ decisions. Management agents are subject to multiple biases that affect the way they perceive events, act upon them and learn from experience. These behaviours cannot be ignored since they have disastrous consequences for organisations. When faced with complex decision, individuals engage in simplifying strategies. Adaptive decision making in real-world contexts relies on strategic simplifications of decision problems. Yet, neural mechanisms that shape these strategies and their implementation remain largely unknown. Although we now know much about how brain encodes specific decision factors, much less is known about how brain selects among multiple strategies for managing computational demands of complex decision-making task. Expansion of behavioural managements parallels development of cognitive science. Neuromanagement has bridged the contrasting fields of managements and psychology. Managements, psychology, and neuroscience are converging today into a single, unified discipline with the ultimate aim of providing a single, general theory of human behaviour. This is the emerging field of Neuromanagement in which consilience, accordance of two or more inductions drawn from different groups of phenomena, seems to be operating. Economists and psychologists are providing rich conceptual tools for understanding and modeling...

References: Glimcher, P.W. and Rustichini, A. (2004) Neuro - management decision making: consilience of brain and decision. Science 306, 447–452
Camerer, C
Glimcher, P.W. (2003) Decisions, Uncertainty, and the Brain: The Science of Neuro - management decision making, MIT Press
Von Neumann, J
Olds, J. (1977) Drives and Reinforcements: Behavioural Studies of Hypothalamic Function, Raven Press
Colle, L.M
Tobler, P.N. et al. (2005) Adaptive coding of reward value by dopamine neurons. Science 307, 1642–1645
Tremblay, L
Roesch, M.R. and Olson, C.R. (2004) Neuronal activity related to reward value and motivation in primate frontal cortex. Science 304, 307–310
Cromwell, H.C
McCoy, A.N. et al. (2003) Saccade reward signals in posterior cingulate cortex. Neuron 40, 1031–1040
Knutson, B
O’Doherty, J. et al. (2001) Abstract reward and punishment representations in the human orbitofrontal cortex. Nat. Neurosci. 4, 95–102
Delgado, M.R
Elliott, R. et al. (2003) Differential response patterns in the striatum and orbitofrontal cortex to financial reward in humans: a parametric functional magnetic resonance imaging study. J. Neurosci. 23,
Kringelbach, M.L. et al. (2003) Activation of human orbitofrontal cortex to a liquid food stimulus is correlated with its subjective pleasantness. Cereb. Cortex 13, 1064–1071
Rilling, J.K
Mark, T.A. and Gallistel, C.R. (1993) Subjective reward magnitude of medial forebrain stimulation as a function of train duration and pulse frequency. Behav. Neursci. 107, 389–401
Montague, P.R
Braver, T.S. and Cohen, J.D. (2000) On the control of control: the role of dopamine in regulating prefrontal function and workingmemory. In Attention and Performance (Monsell, S. and Driver, J., eds), pp. 713–737, Academic Press
Aston-Jones, G
Yu, A.J. and Dayan, P. (2005) Uncertainty, neuromodulation, and attention. Neuron 46, 681–692
Merlo, A
Falkenstein, M. et al. (1995) Event related potential correlates of errors in reaction tasks. In Perspectives of Event-Related Potentials Research (Karmos, G. et al., eds), pp. 287–296, Elsevier
Carter, C.S
Holroyd, C.B. and Coles, M.G. (2002) The neural basis of human error processing: reinforcement learning, dopamine, and the error-related negativity. Psychol. Rev. 109, 679–709
Miltner, W.H
Peyron, R. et al. (2000) Functional imaging of brain responses to pain. A review and meta-analysis. Clin. Neurophysiol. 30, 263–288
Gehring, W.J
Yeung, N. and Sanfey, A.G. (2004) Independent coding of reward magnitude and valence in the human brain. J. Neurosci. 24, 6258–6264
Kahneman, D
Breiter, H.C. et al. (2001) Functional imaging of neural responses to expectancy and experience of monetary gains and losses. Neuron 30, 619–639
Holroyd, C.B
Knutson, B. et al. (2005) Distributed neural representation of expected value. J. Neurosci. 25, 4806–4812
Berns, G.S
Schall, J.D. (2001) Neural basis of deciding, choosing and acting. Nat. Rev. Neurosci. 2, 33–42
Shadlen, M.N
Roitman, J.D. and Shadlen, M.N. (2002) Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J. Neurosci. 22, 9475–9489
Sugrue, L.P
Gold, J.I. and Shadlen, M.N. (2001) Neural computations that underlie decisions about sensory stimuli. Trends Cogn. Sci. 5, 10–16
Brown, E.T
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