Perceptual Control Theory - The Methodology of Modeling, and PCT As Model

The Methodology of Modeling, and PCT As Model

The principal datum in PCT methodology is the controlled variable. The fundamental step of PCT research, the Test for controlled variables, is the slow and gentle application of disturbing influences to the state of a variable in the environment which the researcher surmises is already under control by the observed organism. It is essential not to overwhelm the organism's ability to control, since that is what is being investigated. If the organism changes its actions just so as to prevent the disturbing influence from having the expected effect on that variable, that is strong evidence that the experimental action disturbed a controlled variable. It is crucially important to distinguish the perceptions and point of view of the observer from those of the observed organism. It may take a number of variations of the Test to isolate just which aspect of the environmental situation is under control, as perceived by the observed organism.

PCT employs a black box methodology. The controlled variable as measured by the observer corresponds to a reference value for a perception that the organism is controlling. The controlled variable is thus an objective index of the purpose or intention of those particular behavioral actions by the organism—the goal which those actions consistently work to attain despite disturbances. With few exceptions, in the current state of neuroscience this internally maintained reference value cannot be directly observed as such (e.g. as a rate of firing in a neuron), nor have all of the relevant electrical and chemical variables been traced by their specific pathways while a living organism is engaging in what we externally observe as behavior. However, when a working negative feedback system simulated on a digital computer performs essentially identically to observed organisms, then the well understood negative feedback structure of the simulation or model (the white box) is understood to demonstrate the unseen negative feedback structure within the organism (the black box).

Data for individuals are not aggregated for statistical analysis; instead, a generative model is built which replicates the data observed for individuals with very high fidelity (0.95 or better). To build such a model of a given behavioral situation requires careful measurements of three observed variables:

q_i

The input quantity, that aspect of the stimulus which the subject perceives and has been demonstrated to be controlling.

q_o

The output quantity, that aspect of the subject's behavior which affects the state of q_i.

d

The disturbance, a value summing the effects that any other influences in the environment have on the state of q_i. In a controlled experiment one aims to have just one disturbing influence that is under the control of the investigator, but in naturalistic observation the situation is frequently more complex.

A fourth value, the internally maintained reference r (a variable ′setpoint′), is deduced from the value at which the organism is observed to maintain q_i, as determined by the Test for controlled variables (described at the beginning of this section).

With two variables specified, the controlled input q_i and the reference r, a properly designed control system, simulated on a digital computer, produces outputs q_o that almost precisely oppose unpredictable disturbances d to the controlled input. Further, the variance from perfect control accords well with that observed for living organisms. Perfect control would result in zero effect of the disturbance, but living organisms are not perfect controllers, and the aim of PCT is to model living organisms. When a computer simulation performs with >95% conformity to experimentally measured values, opposing the effect of unpredictable changes in d by generating (nearly) equal and opposite values of q_o, it is understood to model the behavior and the internal control-loop structure of the organism.

By extension, the elaboration of the theory constitutes a general model of cognitive process and behavior. With every specific model or simulation of behavior that is constructed and tested against observed data, the general model that is presented in the theory is exposed to potential challenge that could call for revision or could lead to refutation.