towards a process paradigm in psychophysiology

International Journal of Psychophysiology, 9 (1990) 209-223

Elsevier

209

PSYCHO 00286

Review

Towards a process paradigm in psychophysiology

Kieron O’Connor HSpltal Louis-H. Lafontaine, University of Montreal, Montreal, Que. (Canada)

(Accepted 8 August 1989)

Key words: Psychophysiological process; Effect approach; Empiricism; Deduction non-probabilistic method; Experimental design

This article discusses a theory and method for classifying psychophysiological phenomena as processes prior to considering them

as experimental responses. The initial aim then is to construe experimental units as continuous subject-centred processes whose

beginning and end depends on the individuals’ actions. Boundaries of such processes are systematically defined by first identifying

the process as a dimension. Activities are then classified relative to this dimension. Process units are specified by considering two

classes of activity which form opposite ends of the dimension of process. The two classes are equivalent in all respects save along the

one dimension. These two classes are termed ‘pro’- and ‘null’-equivalence and are the process methods version of familiar H, and Ha

of hypothetico-deductive procedures. Proportional presence or absence of a parameter value during pro- and null-equivalence of a

process is the basis for inferring that a particular measure does or does not typify the process. Actual parameter values of a measure

can then form credible limits by which to classify other processes as equivalent or not. These limits can indicate for example whether

two experimental effects are dealing with the same or a different process.

There are some difficulties in applying this process method, but the general conclusion is that classifying psychophysiological

responses at the outset in terms of process clarifies technical and inferential issues in experimentation.

INTRODUCTION

Psychophysiologists frequently wish to study behaviour as a process rather than as a series of responses. For example behaviour in naturalistic environments outside of the laboratory setting may be better ascribed to social-interpersonal processes than to discrete effects. Similarly, the constituents of a skilled motor performance, e.g. sport, can be viewed as self-regulating processes (involving for example aiming or throwing actions) rather than as responses.

But quantifying behavioural process within a real life context causes problems for conventional psychophysiological designs more suited to explor- ing static experimenter-defined effects in a restric-

Correspondence: K. O’Connor, Hbpital Louis-H. Lafontaine,

University of Montreal, Montreal, Que., Canada HlN 3M5.

tive setting. It is not clear, using such methods, how one defines a complete process as a unit in the absence of stimulus or time markers to give uniformity or how measures taken during complex process episodes can be compared and tested for effects.

Also considering individual differences as more than just artefact becomes important in voluntary actions and in tying personal meaning to physiological responses (viz. e.g. Haynes and co-workers, 1983; Hatfield et al., 1987; Winter and Yack, 1987). This paper suggests that classifying psychophysiological activity in terms of person-centred active processes might aid measurement in these more naturalistic settings.

Discovering process is usually associated with an explanatory theory of underlying mechanisms developed after rather than before experimentation. But I argue that in fact experimental discovery of new phenomena can only occur if there

0167-8760/90/$03.50 0 1990 Elsevier Science Publishers B.V. (Biomedical Division)

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is a prior knowledge of process. Furthermore, if explanation precedes adequate description of process, then invalid inferences about psychophysiological phenomena may result. The middle section of the paper pursues this point and discusses how interpretation of effects and inference in psychophysiology is improved by extablishing prior process. The final section outlines theoretical as well as methodological benefits to treating all psychophysiological measures as part of a process in the first instance.

Process from a descriptive view is the flow of actions which form the background context of any response. The initial section outlines one approach to identifying such process for experimental purposes; setting up boundaries and constraints on processes for comparative purposes; and using non-probabilistic statistics in quantifying information on process.

THE PROCESS APPROACH

The process approach begins by describing the psychophysiological subject matter as a process. There are 3 steps involved: (1) identifying the subject’s activity during the process; (2) placing systematic boundaries on the activity to create a comparative unit; (3) quantifying aspects of the process as a psychophysiological dimension.

(I) Identifying process A process is identified by empirical observation

in much the same way that processes are identifiable in every day life. A recent Irish beer advertise- ment featured under the heading ‘thought process’ 9 photoshots of a glass filling up a quarter at a time then emptying by similar amounts. The ad- vertisers here were relying on our identification of drinking as a psychophysical process. Three basic criteria seem involved in such identification of process both in conventional and scientific wisdom.

Firstly a process must form some continuous sequence of activity, the component activities for- ming different stages, separate steps or changes in amount along a single dimension. So the process

of breathing is made up of stages in filling and then emptying the lungs.

Secondly, a process must have at least one feature of activity that is unique, and hence marks it out clearly from competing processes. This feature may depend on how the process is classified, and the feature may be any type(s) of characteristic relating to function, style, content of activity. For example the process of drinking is char- acterized by several unique qualities concerning the voluntary ingestion of fluid.

Thirdly, it follows that a process must have an identifiable beginning and end. One process finishes and another begins. The process of eating begins with mastication and ends with swallowing after which the process of digestion begins with peristalsis and ends with absorption in the small intestine.

(2) Defining psychophysiological boundaries on the process

In order that there should be agreement on the actions and events that constitute the process, the boundaries of any process can be defined systematically by constructing process units through what I term the ‘null-equivalent’ procedure. The null-equivalent is effectively the empirical opposite to the process. But in specifying its opposite, one defines the dimension of process being in- vestigated. Indeed unless a null-equivalent can be specified, it is doubtful that any process is being measured. If I do not know when a subject is not for instance ‘making decisions’, then I cannot know when a subject is in the process of decision making. Equivalent measures must identify both the process and its null.

This binary logic is most familiar in hypothesis testing. In a sense the process and null-equivalent correspond to empirical versions of the hypothetical binary propositions H, and H, which describe the expectations of how effects relate to hypothetical processes. But H, is usually negatively defined as the complement of H,, whereas pro- and null- processes are positively defined equivalents. So at the outset of the process method we begin with a description of process, rather than postulating binary hypothetical effects. The process rationale is best illustrated by example. Let us suppose I plan

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to measure the effect of a distracting tone stimulus on heart rate (HR) and muscle activity (EMG) during a self-paced lever-pressing operation. My null hypothesis is that there is no difference between tone and no-tone conditions. Naturally, I can ensure that these conditions will be distinct because the experimenter’s actions control auditory presentation. I know exactly when auditory delivery will be the same or different. Now what about the process of lever-pressing? How do I know whether each lever-press involves the same process. I might argue that I instruct the subjects carefully, each one employs the same muscle groups. The apparatus, posture, seating arrange- ments are identical, so the lever-pressing must also be so. But this argument assumes that lever- pressing is a physical affair when instead it is a psychophysiological affair. So standardizing physical environment cannot guarantee whether different psychological processes are taking place. Only classifying lever-pressing as a psychophysiological process can provide such a guarantee. This means identifying my psychophysiological measures as part of a lever-press process before I begin to examine any effects.

Lever-pressing involves placing fingers round the lever, pressing it forward, and then releasing the fingers. This is a very general statement about lever-pressing and does not specify adequately where the boundaries of the pressing begin and end. Do they begin with finger contact on the lever or with initial arm movement or with preparation preceding movement? In deciding how to specify lever-pressing more precisely, I must decide exactly how I wish to classic the process. Am I for example viewing pressing the lever as one of a class of pushing acts? Am I considering it as one of a class of accurate finger movement tasks? Am I dealing with it just as a general motor act as compared with say non-motor acts? By describing the process as one of a class of processes I identify the unique aspect of this process which engages my current interest. In this way I classify the process in terms of one of its unique characteris- tics. If the characteristic I am concerned with is force of push, then I need to describe the lever- pushing as one of a class of forceful acts. I will be defining it by comparison with a null-equivalent

act whose degree of force differs. If I choose speed as the unique aspect of this process, then my description of activity will focus on speed. My null-equivalent comparison units will differ in units of speed.

I am considering subject initiated activity. The attribute by which I classify the activity is then

naturally an active one. Because it is an action and hence the person can choose whether to do it and

by what degree it is to be carried out, I am justified in considering this active attribute as a dimension. Since the process episode is defined by the person’s activity, this requires the subject’s active cooperation and means positively engaging and maybe training the subject rather than just telling them what not to do. The subject is not considered a passive sensor of information and much more attention is focused on activity usually lumped under the phrase subject ‘sitting comfor- tably’. Under this ‘active agency’ perspective, even sensory processing involves ‘acts’ of some kind. Since we are interested in typifying the person’s own behavioural process in a particular situation, we wish to include as much activity as can be observed within the process. A physiological measure cannot be ‘contaminated’ by behavioural activity going on at the same time if that activity is part of the same process. If when I ‘pay attention’ to a particular phenomenon I clench my jaw and bite my lip - then these are acts associated with attentional process in my case. It may be a revela- tion to know that I can pay ‘attention’ without biting my lip. But in changing or constraining activity I am qualitatively changing my attentional process.

Because in the first instance description of the psychophysiological act is person-centred, and in- cludes everything the person is doing, the experimental context does not become any smaller because the process unit is small. The process unit could for example encompass a whole night’s sleep or watching several lights and pressing buttons or moving the little finger once. It is equivalence of process description which guarantees comparative units rather than uniformity in length or duration. In process design the guiding and controlling influence on the experiment is the specificity of the initial process chosen as the experimental unit.

Rnlr? exteil4 -ntdti 4’ n t1qP’II RalrP extrn4 rrst*ti B”J tlg-ltli

Fig. 1. Raw biceps root mean square EMG data from one subject during two episodes of a lever-pressing operation dur-

ing which the subject gripped the lever tightly or lightly.

Defining the process in a meticulous fashion makes the experimenter clear on which particular aspect of behaviour she/he is concentrating.

Having decided on the unique dimension of the process. I now specify, as far as I and the subject are able, the active strategy on the part of the subject involved in producing opposite dimensions of the process. That is to say I use my prior knowledge to specify an activity that will produce a fast lever-press or a slow press or a forceful lever-press. In the present example (Fig. 1) I have chosen to view lever-pressing as one of a class of manual pushing acts. The null-pro dimension is hence pushing and the null episode is some mutually exclusive variation on pushing; in this case pushing lightly. The process act involves lifting the arm about 6 inches from a table, extending the forearm, rotating the wrist outwards, opening the hand, gripping the lever as tightly as possible and pushing it along a slot. The null act is the same actions but with the person gripping the lever lightly. Both episodes take approximately 6 s.

The aim in recording muscle activity along this dimension is to see if it too typifies the presence

and/or absence of this personal dimension of force. Do the limits of the measure differ between process episodes and null-equivalent episodes? If so then they are a psychophysiological descriptor of this lever-pressing process.

(3) Quantifying information on process It may be that the experimenter already has

strong prior knowledge of the likely limits of a parameter within the two null and pro processes. In this case specifying the limits may be simply a case of stating prior knowledge of the process context. However, although an experimenter may be certain about some values of a parameter that lie in or outside a process, deciding on an exact boundary between two processes may be more difficult.

The decision on the actual limits of a measure during null- and pro-equivalent can be made according to Bayesian-type decision theory where the frequency of occurrence together with prior knowledge can decide most likely values (O’Con- nor, 1985). The extent of prior knowledge will decide how many episodes I need to consider before reaching a decision on the psychophysiological boundaries of the process. If prior expectations are high, and the process specifically defined and the subject trained in actions prior to recording, the decision-making about a process may only require one episode. This observed range of values is relative only to the particular behavioural process described.

Both pro- and null-equivalent EMG plots in Fig. 1 are each based on 480 data points. These plots represent my entire parameter space for each equivalent action. In process description all information during an act is relevant information. The observed parameter space is my entire population. It is the unique context of this process. Hence all inferences are based on the complete space, not on, say, one value taken to ‘represent’ the others.

Number of observations is important only in so far as the number is sufficient to cover the entire process. Time is relevant only in so far as it is a condition of equivalence. In the present example it is stages of the operation which are the basis of equivalence and the timing is not identical. In fact these EMG recordings were made with one re-

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hearsal. However, since the observed pro and null actions of the person were equivalent, I base my decision about EMG equivalence on the same actions and can do so on this one episode. There may be reasons for obtaining more than one repetition but they are not the same reasons as in the variance case. Robustness does not necessarily follow from repetition indeed not even in the variance case (Morrison and Hankel, 1970). If somebody performs an action in front of me I do not usually ask them to repeat it several times to be sure it happened. Amongst the reasons I may wish for a repeat are: the event was so remarkable and outside of my expected limits that I distrust its appearance; some interference (internal/ external) obscured observation of the action; I wish to change some part of the action or at least change my perspective on the action. As Edwards et al. (1962) have pointed out there is nothing to be gained from ritual repetition of events after one has gained enough evidence to make a decision.

It might be objected that I should repeat the pro- and null-equivalent episodes at least twice in order to balance order of appearance. After all, it is not unlikely that the effect of performing the pro first may influence performing the null. Again this is immaterial in the present context. The two equivalents (pressing lightly/forcefully) are mutually exclusive actions at all times (one can never press both light and forcefully at the same time under any circumstances) so if the EMG parameter is to typify the actions it must also be mutually exclusive at all times. Any constraints on the process (e.g. that the limits only apply in some circumstances) will be implied in the specific way I describe the actions of the episode not in the measures I take. This attention to micro-behaviour, discussed previously, is essential because limits are only relevant to the process described.

Looking at the plots (Fig. 1) it is fairly evident that the biggest divergence in the pro and null waveforms is during the gripping operation at the end of the process action. However, any measure of equivalence must include the whole process behaviour, not just selected points of difference, since the entire parameter space is my population, and hence the background context to which any differences refer. Since the two processes are

TABLE I

Proportion of data points lyrng above each of 6 categories of

EMG o&e

Below the proportions are the 2-unit support limits (2&(1 -

p)n) which guarantee a-compatibility of process at 95% for

proportions falling within those limits. The values are given for

two repetitions of pro- and null-equivalent of the activity

shown in Fig. 1

EMG values (p V)

> 1.5 > 12.5 > 11.5 > 22.5 z 21.5 t 32.5

Pro 1 0.91 0.68 0.41 0.26 0.14 0.06

Limits * 0.016 0.046 0.044 0.040 0.032 0.022

Pro 2 0.95 0.11 0.40 0.25 0.13 0.07

Limits * 0.020 0.042 0.044 0.039 0.030 0.024

Null 1 0.92 0.55 0.18 0.05 0.01 0

Limits f 0.024 0.046 0.034 0.020 0.009

Null 2 0.96 0.51 0.22 0.08 0.03 0

Limits f 0.019 0.044 0.031 0.024 0.016

largely equivalent there is a lot of overlap in EMG values and it is differences in proportion of com- mon attributes rather than absolute differences that provide limits on each process. The limits are provided by differences in proportional presence or absence of the EMG measure. I have chosen amplitude as my measure and Table I gives cumulative proportions of amplitude values in 5+V steps rather like a frequency distribution. So for example 0.55 of my null-equivalent and 0.68 of my pro-equivalent were above 12.5 pV. By definition since these are the proportions observed they are the most possible proportion (= p) given this parameter space for null and pro respectively. However, there are other proportions less possible that may if observed in other samples qualify that episode for membership of the same class of process as the present one. These limits on process can be established by non-probabilistic (N-P) methods.

Statistical considerations

N-P methods talk of proportions not probabilities. There is no question of considering events in terms of probability models. (Definetti [1974], generally considered the founder of N-P methods, argued that probability does not exist). N-P methods adopt what Rouanet (1982) terms a set-theo-

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TABLE II

Injerences about future action that can be mode from changes in process boundaries associated with signrficanr or non-significant effects

No process Change in process No change in process

Significant effect

Non-significant effect

No parameter space (context) Effect can be qualified in terms Re-examine definition of process: available to interpret effect of pro or null end of dimension effect not notable in

depending on which changed terms of this process

Nothing can be said Subtle change in process; No change on this about the data re-examine hypothesis: process using this parameter

look at individual differences

in change; novel phenomenon

retie approach which can establish credible limits on the basis of the possible samples that could exist in a space equivalent to the one observed for which proportions may be greater or less than observed proportions.

So for each set of possible proportion (@ = 0, l/n.. . n - l/n, 1.) I can calculate support limits (fi(1 - p)/n) and an associated support curve. For any future set (F) of observed relative fre- quencies (f), these support limits yield an equivalence property where the property defines a binary relation on the Cartesian product F X @. For a given f, this relation will discriminate those proportions observed which are cY-compatible from those that are not at a certain level of guarantee. Proportions observed outside the limits given in Table I are unlikely to be the same process at a guarantee of 95%.

Using the limits established on process and null for this sample, I can then compare other proportions from other samples to establish their equivalence. In Table I for the proportion of amplitude above 12.5 PV it is clear that null and pro- epi- sodes are outside of each other’s process limits, but repetitions of null and process episode (null 2, pro 2) are a-compatible to the first episode and hence can be considered equivalent to null 1, and pro 1 respectively.

The logic here is very similar to creating a likelihood or ‘support’ distribution by computing likelihood ratios from comparison of complemen- tary event probabilities (Edwards, 1972). In the present case, however, the comparison is between possible actions the person can perform in the

same process. Statistical likelihoods are computed from conditional probabilities where probability is a uniform vector from O-l. The conventional probability model assumes a binary symmetry between event and non-event. The probability of an event occurring is considered the complement of the event not occurring, in order that occurrence and non-occurrence can be contained along a uniform scale from 0 to 1. But in empirical terms the non-occurrence of one event means the occurrence of another event and in process terms these may be qualitatively different acts. Possible actions can be identified solely on the basis of observation of what is most and least possible, whereas probability is always hypothetical. In practice when the decision is made on whether a measure typifies the process A, this does not mean typical of A com-

pared to ‘not-A’ its complement, but A as compared to B its null-equivalent. Refinement of a process through increasingly accurate specification of actions would result in a distribution of maximum and minimum possible values for a series of dichotomous null- and pro-equivalents activities. A different set of possible psychophysiological limits would apply depending on how gross or refined the definition of the process unit. Maxi- mum possibilities have all the benefits of likelihoods in that they can be combined across qualitatively different process episodes. The maximum possibility of one subject’s process may be different from another’s, but they can be combined to give an additive description. A maximum possibility of one process may be conditional on the presence of another in which case they can be

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combined multiplicatively. (viz. O’Connor, 1985, 1989 for further details)

THE RELEVANCE OF PROCESS TO THE IN- TERPRETATION OF EFFECTS

The main contribution of the process approach to experimentation is that it relates hypothetical effects to a context, in the form of a definite parameter space. There has always been a tendency to assume effects apply to absolute values of a parameter when in fact they can only apply to a given space (Steger, 1971). The issue of identifying this space can be clarified by process methods. Process methods also help in revising hypotheses, since they place hypotheses in an empirical context, and disallow reliance on vague abstract constructs.

Table II gives an indication of how knowledge of process aids interpretation of effects. There are basically 4 possible outcomes of process under either a significant or insignificant effect. Either pro or null or both may change limits or not change limits. A significant effect with no knowledge of process limits leaves no firm context in which to interpret the effect, only a general idea as to what process or classes of process the effect relates. A significant effect and a shift in process (the most likely case with a single dimension of process) allows the effect to be qualified in terms of how the process changes. If the pro boundaries change but not the null then the effect is most pertinent to that part of the dimension repre- sented by the pro. If it is the null limits which change then clearly more attention should be paid in future to what was termed the null. If both change then the context of change incorporates both pro and null and may relate to wide context including the whole process dimension. It might be possible to qualify any change in process more concretely and say to which process the boundaries have changed. This may be particularly useful in the case of comparing effects on different skill levels. In skill acquisition variation of components sometimes reduces over time as a consequence of stability of process. This causes problems for the conventional variance statistics because of non-

I

Practice

Stage 3

7b

Stage 2

Stage 1

9'0

bpm

Fig. 2. A process boundary of heart rate has been established for a lever-positioning movement and its null-equivalent (not

positioning a lever). The process boundary is then narrowed

during 3 stages of practice. Each stage representing 4 repe-

titions of the process. The successive boundaries reflect the possibility distribution of heart rate values along a dimension

of practice.

stationarity, development of trends and changes in sphericity. Fig. 2 gives an example of the stabiliza- tion of process with practice and a refinement of measures. Within the process episode, consistent practice in 3 stages has narrowed the range of heart rate recorded. In other words the most and least possible proportions of some heart rate values are different depending on whether process and null actions are compared in stages 1, 2, or 3. There is a change between the 3 stages in the limits of heart rate values between 72-75 and 84-87 b.p.m., indicating that limits on these values show no equivalence between different stages. However, when considering limits of 78-81 b.p.m., there is equivalence of process. So episodes differ- ing in variability can still be connected to the same basic process. The method can then dis- tinguish stimuli that change process from those which affect variance.

Knowledge of process limits may be the only guide to further action if there is no significant effect. If an effect is insignificant, I must conclude in accordance with the null-hypothesis that the intervention has had no significant effect on the measure. But what now? One of the many criti- cisms about null-hypothesis testing is its inability to say anything about data that is not significant.

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In other words it is asymmetrical. In fact nothing more can be said about the data or about what to do next, though a non-significant finding raises just as many questions as a significant one. Should more trials be considered? Should there be a smaller dose? Were room temperature, prior arousal, personality, sex, time of day, posture, electrode position adequately controlled? In practice the experimenter will draw on prior experience, guess-work, and possibly illicit comparisons to salvage some decision on future behaviour from the data. But the hypothetico-deductive method allows no further interpretation. Knowledge of process accords a symmetry to the experimental findings in the sense that one can make a positive statement in support of the null hypothesis that the process is not being affected.

On the other hand there may be a slight consistent change in process boundaries but without effect, and this could suggest modifying this intervention rather than abandoning the hypothesis. In a recent experiment on preparation to respond, I had established the credible limits of an EEG parameter space where my pro was preparing to push a lever the null preparing to keep it in place. The intervention was smoking and though there was no effect between smoking and non-smoking conditions the boundary of the null went upwards during smoking. In other words activity shifted more towards process of preparing to push than to not push. Changes in the boundaries of the process of preparation were established by the null- equivalent - when the person was not preparing to push the lever. This interpretation would not have been evident in a straightfoward comparison between conditions but became apparent by lin- king two ends of the process dimension. In ad- dition the process boundary changed in some but not other subjects. Individual differences in process may mask change in effect but this between- subject information can be systematized in terms of process. Rouanet and Lecoutre (1983) suggest the major contribution of the Bayesian approach is that a genuine conclusion in favor of some (approximate) null-hypothesis can effectively be attained, and differentiated from those situations where, owing to insufficient information, no such conclusion can be reached.

A change in process with no corresponding effect could indicate a novel phenomenon, since the change indicates that factors other than those hypothesized by the experimenter are affecting process. These factors may be a function of measurement or may constitute some new response. An example here is the discovery of the contingent negative variation (CNV) by Walter and co- workers during a conditioning paradigm. The CNV was not an effect of conditioning but nevertheless involved a change in the expected level of the EEG during interstimulus interval. This change related to processes other than conditioning. If in such a case pro limits of a measure changed but null limits did not, this would further aid discovery of a phenomenon since the equivalence between null and pro in all respects except the change in parameter limits would help counter arguments that the phenomenon was artefact, as happened initially in the CNV case.

One way in which relating effects to processes can aid further courses of action is in the formula- tion of hypotheses in model testing. For example I recently wished to compare two models of the effect of smoking on heart rate during task performance: one that it was mediated by attentional process; the other that it was mediated by motor preparation. In theory, attention and motor preparation are distinct processes, and in theory-led experimentation, experimental conditions would be designed with hypothetical distinctness in mind. However, it is not clear from a subject’s point of view that attending is purely sensory or readiness purely motor and that attending does not involve in some way motor processing or that motor processing does not involve attention. A conventional design might employ two levels of attention and two levels of response preparation and compare effects within and between conditions. Any- thing less than a clear-cut effect between both conditions would leave interpretation difficult. Even with a clear-cut effect one would be unsure without further experiments as to precisely what attentional or motor preparatory process the effect generalized.

An alternative would be to establish both ‘attention’ and ‘motor preparation’ acts within an equivalent process context. The first advantage

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here of specifically describing the acts in terms of personal strategies would be to ensure that the classification of ‘attention’ and ‘preparation’ were realistic not hypothetical. So for example an attention process could be described specifically as: sitting down, looking ahead focussing on sequences of events on a VDU. The process of preparation to respond could likewise involve sitting down, looking ahead focussing on the same sequence of events but responding to the sequence. This would establish a process equivalence along a dimension of ‘attending whilst preparing to move’ to ‘attending whilst not preparing to move’. Once established, independent EEG limits for these attention and preparation processes could form the basis for refining attention and preparation further, and then contrasting the effects of an intervention.

Another important contribution of the process approach is the potential for establishing equivalence between effects in terms of process. Two effects may be significant and quantitatively similar but change process in qualitatively different ways. If, however, two interventions have equivalent effects on a process boundary, in other words affect the limits in a cY-compatible way, then they may be considered response-equivalent for this parameter space. This is particularly useful in the clinical field where one might wish to establish identity of a class of equivalent behaviors, for example, in planning desensitization, or where one might like to substitute one intervention for another.

THEORETICAL CONSIDERATIONS OF THE PROCESS APPROACH

The psychophysiologist may object to considering psychophysiological responses at the outset as processes and argue that we need to begin with hypothetical processes before we can progress to empirical process. I argue no, for these following reasons.

Firstly: the notion that empirical process can be built up and refined from hypothetical effects is fallacious.

Secondly: interpretation of effects requires a priori, a gestalt of process.

Thirdly: in practice hypothetical processes do not remain hypothetical but achieve an invalid quasi-empirical status through the use of measures as operational constructs.

In my opinion starting with hypothetical processes will actually mask rather than facilitate description of empirical process. I suggest that in psychophysiology we must always start with some description, no matter how crude, of actual psychophysiological process and I shall now examine these arguments in more detail.

(I) Description of process cannot be built up from knowledge of effects

Some confusion may exist about how one iden- tifies process because of the split accepted between physiological and psychological process. An ongoing EEG or EKG may be viewed as a physiological process and perception of a signal source as a psychological process. A dip in the EEG or a change in t-wave amplitude following perception of a signal are psychophysiological effects. But where are the psychophysiological processes associated with these effects? Perhaps there is a tendency to see process as already given in the presence of separate physiological and psychological processes. But this cannot be so, if psychophysiology is to have the status of a distinct science. Neither is it the case that knowledge of effects can adequately substitute for process, though popular misconceptions about deductive science may be misleading here.

The way in which experimental science builds up a picture of a complete phenomenon, piece- meal fashion, might be likened to several blind- folded people feeling different parts of an elephant (Ornstein, 1972). Eventually, gathering enough samples of information, they would all agree on their definition of the complete elephant. But this analogy would only work if we already knew what an elephant looked like. In reality without such knowledge each person’s observation would become the centre of its own conceptual ‘elephant’ and as the effects of further manual prodding and squeezing were collated so each separate elephant would become strengthened in its hypothetical

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insularity from all others. As evidence we may turn to ongoing debates about whether certain electrocortical measures are products of attention, expectancy, or preparation, where the same data seem to accentuate rather than resolve argument. Such experimental controversies often seem semantic functions of author’s conceptual frame- works rather than of the phenomenon itself (see Macar and Besson, 1985).

(2) Interpretation of effects requires a priori ‘u gestalt’ of process

Knowledge of process must precede knowledge of effects if the latter is to be in any way scientifi- cally meaningful, since in practice identifying the cause with an effect depends crucially on how I define the context of the effect. This requires an understanding of the underlying process which

unites cause and effect. As an example take the classic case-study of

cause and effect: one billiard ball hitting another. Here, apparently, we have two separate events: one ball rolling and the other ball being hit into the pocket by the first. But before we can under- stand this as cause and effect we must have an a priori understanding of the processes involved in one ball hitting another into a pocket, otherwise amongst other points the division into two ball units is meaningless. (Why not start the causal chain with the player aiming the cue?) Hence in this context a ball hitting another ball into a pocket must be understood as a single process before cause and effect can be ascribed. If a unit of cause and effect is not defined by some coher- ent understanding of process, the causal context has no logical beginning or end.

Empiricist philosophers from Hume to Popper and Harre seem agreed that the only meaningful cause is the one involved in the regulation of process, otherwise there are as many causes as can be inferred and this leads to infinite regression (Popper, 1963). The implication for S-R paradigms is that in the absence of understanding the processes connecting stimulus and response to stimulus and response cannot assume the role of cause and effect. Explaining a skin conductance event as being caused by a light may be confusing two independently observed phenomena, namely

seeing a light and making a skin response. Con- necting them by a hypothetical cause does not alter what is observed, rather it redefines one phenomenon in another’s context, which is empirically pointless. Evidence is lacking for assuming a priori that two independent psychophysiological events are related just because they occur sequentially in time (see Jamieson, 1987).

(3) Hypothetical processes gain un invulid empiricul status viu operational constructs

Some idea of process must precede deductive or any other kind of explanation. Therefore, if this a priori conception of process cannot be provided empirically it is constructed hypothetically. But starting with hypothetical process confuses description with explanation because hypothetical processes in psychophysiology tend to be interpre- tative rather than descriptive. Do we know for example when the psychophysiological processes of arousal, or attention or expectancy, or habituation actually begin and end, or what unique ob- servable attributes characterize a state of expectancy as opposed to attention or arousal or preparation? Can these processes be identified as self-contained phenomena without the help of other markers, operational definitions, a priori assumptions? I would say mostly no. But even if they can be, few who study the effects on these processes bother to describe them empirically at the outset. More likely an experimental effect of some unknown psychophysiological phenomenon is explained by way of operational definition of a hypothetical process. Change in EEG frequency or skin conductance level is often taken as an operational measure of arousal. But such changes may reflect a number of processes, depending on context, and the changes cannot always be taken as measures of arousal. The operationalizing. which after all involves real measures, gains for the hypothetical process some empirical face-validity and thus leaves it in a kind of quasi-empirical limbo. In some cases the measure may even become the hypothetical processes it is supposed to oper- ationalize. The appearance of an alpha rhythm becomes ‘proof of’ an ‘alpha state’. In this way many constructs end up leading a triple existence and manage simultaneously to be a source state,

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explanatory construct, and descriptive phenomenon.

Take for example the process of habituation. The observed reduction in response to repeated stimuli is explained by the process of habituation. This hypothetical explanation, however, soon becomes a description of a phenomenon in its own right. A subject is said to be habituating. But regardless of the academic merits of habituation, the term is not an observation, it is an explanation of what a subject is doing. An explanation is a misleading account of process because it distracts attention from what the person is actually doing. Each response in a habituation series is actively produced by processes about which we are unlikely to find much so long as we stick to generali- ties. Ben-Shakhar (1980) has suggested that con- tradictory findings in habituation are due to the loose criteria of generalization of habituation. Ben-Shakhar argues that all habituation effects do not represent the same process and suggests adopting situation-specific models. Differences in subject strategy feature in discussions of failure to habituate where it is quite clear that different processes produce similar effects (Spinks and Sid- dle, 1984).

The same objections can be raised in connec- tion with other hypothetical constructs such as arousal. The argument for encapsulating a person’s specific activity within a generic process such as arousal could be that as more becomes known about specific strategies, so the concept becomes less general. But in practice this doesn’t occur. Rather, either the concept becomes more general and is applied to numerous variants of its original activity, as in the case of arousal, or as in, for example, the construct of expectancy, new subcon- structs (e.g. anticipatory function, motor pre- paredness), are introduced to deal with divergent component activities. But these are in their turn equally general. In practice concepts such as ‘arousal’ and ‘habituation’ survive challenges of empirical validity not with increased precision but, with increasing generality, the conceptual significance of concepts themselves often being the last thing challenged (Standing and McKelvie, 1986). The main methodological problem then is that whatever information we might gain by descrip-

tion of the actual psychophysiological process is masked when constraints imposed by explanatory constructs determine units of measurement, cause and effect, and experimental manipulation.

Much of conventional design in psychophysiology is inappropriate because it is premature. It is premature to talk of hypothetical concepts, processes, effects before we have even described an empirical psychophysiological process in the first place. As Mecacci (1983) puts it, we are still in the stage of classification, the Linnean age. We are in the position that agriculturalists were in when they described the processes of plant growth and crop yield before they tested effects of en- vironmental context, and sought explanations. This lack of descriptive psychophysiological process may make more fundamental assumptions in psychophysiology equally premature.

Assuming more than we know in conventional psychophysiology

These are a set of commonly shared assumptions about the nature of psychophysiology which guide experimental life and are evident in criteria for defining, measuring and making inference in psychophysiology. These assumptions are ex- pressed in 3 ways: definitional criteria, (we know what we are doing when we do psychophysiology and that we are not doing something else); methodological criteria, (we know what we are measuring when we measure responses, and we know how to measure them); and inferential criteria, (we know what can be inferred from our data and in what way our theory relates to facts). Controver- sies about improving these criteria tend to focus on the need for more sophisticated technical considerations. But perhaps the more basic concep- tions are a problem. Are we assuming more than we know? Let us first consider the problem of definition.

The problem with accepted definitions of psychophysiology is their cobbling together of hypothetical demarcations between psyche and soma, internal and external, private and public, subjective and objective realms. Ax (1983) for example takes as given that psychophysiology is about translating between psyche and soma, but points

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out that before we can translate between two systems, each system must be well described. The problem is they cannot be well described, because there is no empirical evidence that independent realms of mind and body exist in the first place. Of course conventional wisdom particularly in western cultures accords mental and somatic events to different categories. But empirical criteria would demand that, for example, we know for sure when it is possible to have a private event without some measurable public display, or a mental phenomenon which doesn’t express itself directly in some physical measure.

Psychophysiological evidence such as it is, suggests that it is very difficult to place precise boundaries between, say, physiology and behaviour. The difficulty arises in deciding on what Furedy (1983) terms a genuine rather than operational definition of psychophysiology. Stern (1964, 1983) who produced the first genuine definition of psychophysiology as research in which the dependent variable is physiological and the independent behavioural, admits that he is unclear as to what divides behaviour from physiology, and at what level of operation an organism must be involved, before we can talk of psychological process.

Furedy (1983) notes that it is more convenient for practitioners to offer operational or analogical definitions of psychophysiology since they appeal to subjective arbitrary demarcations and sidestep longer-term issues. His own genuine definition as the study of psychological processes in the intact organism as a whole with unobtrusively measured physiological processes, runs into problems of how much of the organism must be involved for physiology to become psychophysiology. Mangina (1983) argues that drawing artificial distinctions between physiological psychology and psychophysiology is futile semantics. Manipulated variables cannot be limited in their effects by psychological and physiological boundaries.

The issue here is not simply metaphysical. In a sense it is exactly the job of psychophysiology to demystify vague metaphysical distinctions between, for example, mind and body. The point at issue is a practical one. If there is no a priori empirical reason for considering mind and body

as qualitatively distinct realms, then this bi-par- tisan division of the person in psychophysiology serves only a heuristic function. There is then no reason why we cannot consider alternative heuris- tics which do not insist on a priori division and hence on independent manipulation of physical and mental or internal and external variables. We might, for example, consider a dimensional rather than a categorical classification. If, for example, physiology and behaviour, or internality and ex- ternality were part of the some continuum, it would make no methodological sense to investigate the effect of one upon the other. In the same way that it is clearly nonsense to investigate the effect of personality on personality or age on age, since events along a single dimension are considered a progression of the same process.

Another heuristic might be consider mental and physical events both as behaviour. Here the unit of psychophysiological analysis would focus on person-centred behaviour units rather than separate cognitive or physiological units. Of course the value of a heuristic lies in its utility rather than its accuracy. But I would question the utility of any heuristic that saddles methodology with the job of eternally matching units from qualitatively distinct ‘mental’ and ‘physiological’ realms. Per- haps we could start with a genuine definition of all mental and physiological events as psychophysiological phenomena. As yet we do not deal with genuinely psychophysiological phenomena or units in our measures. Rather psychophysiological con- clusions are arrived at on the basis of separate psychological and physiological measures, and this leads to problems with methodological criteria.

We can measure something that exists without knowing any more than our measures tell us about it. But before we can measure something as an effect we must have some idea of what it represents. There must already exist some criterion for deciding relevant from irrelevant measures and for partitioning units. This is particularly so in a formal deductive system, where the role of methodology is to structure observation in accordance with theory. The response represents the effect of an independent variable carefully recorded within a paradigm structured to exclude other variables and to allow comparable future measurement and

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to anchor further observations. But the process on which effects are being measured must already be established as a phenomenon in its own right. This seems to me clear from agricultural origins of earlier Fisherian designs (Fisher, 1935). Put another way, the effect paradigm does not allow for the discovery of a new response phenomenon, and it is not surprising that most recent important discoveries in psychophysiology have been made incidental or tangential to the formal paradigms in which they were discovered. (Papakostopoulos [1980] even termed his discovery a no stimulus no response related potential). Discovery comes from simple empirical observation and decision-making based on experience rather than deductive theoris- ing.

The problem comes when a response phenomenon is identified only by its existence as an ‘effect’ or correlate of some other event. In this case the effect paradigm is not equipped to clarify either what the response represents or whether it exists or not. Prior knowledge of process gives an idea of relevant and irrelevant parameter space. But the lack of a clear conception of a psychophysiological phenomenon outside of its somewhat arbitrary identification in hypothetical paradigms, leaves technical procedures arbitrary and indeterminate. There can be no satisfactory technical/statistical means of controlling behavioural artefact, if un- wanted activity is decided solely by the conceptual constraints of the paradigm. The problem of identifying valid and reliable phenomena from unrelia- ble hypothetical effects adds to the difficulties of standardizing paradigms and developing them into social and ecologically relevant areas, since there is uncertainty defining what should be manipulated (Gale and Edwards, 1986; Martin, 1986). This absence of empirical process not only entails methodological problems but also problems in inference about what responses represent and how effects relate to theory. In order to be fitted into a conceptual framework, we must be sure of what response phenomena themselves represent. In the effect approach we know rather more about what responses do not represent than what they do. We know the ‘effect’ does not have an identity to its cause and there is no one to one correspondence with a stimulus event. But we are unsure as

to what a response does correspond, except that it must be a correlate of something. This tendency to presume that responses are ‘correlates’ of another realm leaves us uncertain whether responses should be interpreted as codes, signs or index markers. As recent debates between Donchin (1982) and Schwartz and Pritchard (1982) point out, there are incompatible epistemological consequences to treating responses as codes or signs or markers. The first suggests a direct translation of some single event, the second that responses are a product of another event, the third that responses are simply general pointers to some gross process. In practice psychophysiologists generally confuse all 3 under the overall rubric of ‘correlate’. But the specific way in which responses represent a correlate remains because the assertion that they are correlates remains hypothetical, not proven. The responses are not identified with an empirical process.

CONCLUSION

I have argued that some current definitional, methodological, and inferential problems might be ameliorated if psychophysiologists start with a description of their psychophysiological data as a process. Some current assumptions about what constitutes independent and dependent variables, or cause and effect in psychophysiology seem to explain their subject matter before they describe it.

The key to describing process within an experimental setting is to reverse the conventional roles of hypothetical and empirical processes, so that the boundaries of the process rather than just the hypotheses are delineated at the outset. This allows psychophysiological activity to be an independent variable and to be described very precisely and complexly, if need be, and also allows the person to be treated as agency. Behavioural controls can then replace statistical controls of variability, and subject’s activity during an experiment described in detailed process terms. Judging from the variety and vagueness of current descrip-

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tions of behaviour during similar experiments testing similar effects, this last factor deserves some attention. In particular Gale and Baker (1981) express concern that differences in peripheral activities may be incorrectly attributed to central processes.

The lack of hypothetical constraints on quanti- fication of activity and the description of units in empirical terms accommodates those wishing to investigate clinical and ecological settings and adaptive processes such as skills acquisition and voluntary motor action. A descriptive dimension of units is also sensitive to subtle changes in process and can measure these changes using non-probabilistic notions of a distribution of possible processes. I think, in the long-run, that

establishing process will bring economy to psychophysiological practice, since it will, for example, reduce time spent in running many trials and many subjects, and also make the decisions on such factors arbitrary. The approach should also allow more to be said about the same data with greater certainty, than at present.

However, the process approach brings its own difficulties. There is the time to be spent training subjects; co-operation for example in specifying process actions might not always be achieved. Closer attention to and monitoring of activity during performance of the process is required. Greater reliance for decision-making is placed on the preliminary logic and expectations formulated by the experimenter rather than on formal significance tests. These factors calling as they do on the patience of Job and the wisdom of Finn combined, also focus much effort on what is generally considered to be merely the preliminary stages of the experiment. On the other hand, establishing the limits of a process may require no more than stating the obvious if current empirical knowledge is strong enough to confidently suggest some

boundary between stated processes and null- equivalents. Of course, most experimentalists see their business as quantifying uncertain rather than certain knowledge. But I suggest that in establishing systematically at the outset what we can be certain of, we may become more confident in our statements about uncertainty.

ACKNOWLEDGEMENTS

The author would like to acknowledge the com- ments of the following on previous versions of this paper: Dr. G. Blowers, Dr. J. Furedy, Dr. R. Jennings, Dr. J. McGuigan. Dr. I Martin, Dr. J. Spinks and Dr. R. Stelmach.

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