As a systems engineer and professional mathematician, I sometimes notice two completely different fields are governed by the same model, equations, or phenomenology. One might never guess that the decomposition of ammonia gas over a platinum screen, has the same underlying equations as freefall from an airplane. This observation is unlikely unless one is exposed to both contexts and happens to also know the fundamental mathematics. By coincidence or luck, sometimes one stumbles into seeing the similarity.
Recently I observed this as a test subject in a medical psychology experiment called "delay discounting".
Recently I observed this as a test subject in a medical psychology experiment called "delay discounting".
These studies characterize addictive behavior by attempting to measure a person's tendency towards impulsiveness and control of same. Impulsiveness is quantified by asking the test subject questions like, "Would you rather have $50 now, or $100 in a week?", on a sliding scale where the impulsive person will take anything in the here and now, rather than pie in the sky after some interval of time. Delay discounting behavior is a useful window into addictive and other human behaviors. Consider the show Survivor, where the contestants will pay $500 for a hamburger if they can have it right now, even if it means risking a million dollars in a few days.
In delay discounting there are four categories of questions. Gain and loss versus time, like the question above, and gain and loss versus certainty of reward.
The stunning (to me at least) observation is that after a subject answers these questions, they have effectively calibrated the gain curves on four specific operational amplifiers.
Amplifiers take small signals as inputs, and subject to variables like feedback, gain setting, and stability, produce large signals as outputs. There is a saying in electrical engineering that, "Amplifiers Oscillate and Oscillators Amplify". One may extend that saying to the world of digital filters to say, "Filters Amplify and Amplifiers Filter".
Without going into an incredibly boring tirade, let me just provide a few assertions that apply to the amplifier model.
1) Clusters of neurons sum their inputs to produce an overall action, and this is similar to amplifying a small input to produce a large output.
2) Different clusters of neurons, responsible for different activities, have different gain settings. The gain settings of these clusters can be imaged using techniques like fMRI and PET.
3) After measuring an individual's gain curves, one could actually predict (the thesis of the delay-discounting world) their propensity to engage in various addictive behaviors.
4) One an individual is characterized, one could simulate the behavior of that person with an analog or digital amplifier.
5) One could create an electronic implant to control addictive behaviors in willing individuals that are afflicted. (Implants in the unwilling are beyond the modest scope of this note!)
Addictive behaviors have a wide range of expression and involve substance and non-substance stimuli (gambling for instance). Basal ganglia disorders like Obsessive-Compulsive Disorders or OCD, may also involve the brain centers connected to addition.
Whether addictive disorders are architectural from brain morphology, neurochemical from nerve cell receptor distribution, or both, I do not know. What I do know is that the amplifier model can be very useful for characterizing both the likelihood and the expression of the behavior in individuals for which the measurements have been properly made.
In that sense, delay discounting measurements provide what engineers call, "A Characterization of the Amplifier".
This would certainly seem a useful model for characterizing behavior, in my mind at least.
Ref: Eisenberg et al. Behavioral and Brain Functions 2007 3:2 doi:10.1186/1744-9081-3-2
