From our analysis
emerges a concept of emotions significantly different from the one commonly
accepted by Evolutionary Psychologists, . Due to our concern with the evolutionary
mechanisms for understanding of some essential features of the information
treatment in the brain, it seems necessary to point out and discuss those
differences.
We refer in
the following to the on-line available texts “Evolutionary Psychology
and Emotions” [1] and “Evolutionary Psychology Primer”
[2], by Cosmides L. and Toby J., which you can find here.
We would like to point out that we agree with many of the ideas of E.P. and
that the following discussion is conceived in order to clarify what are, after
us, some of the “errors” of this approach.
The basic
idea of E.P. about emotions is clearly stated in the first of these texts.
As the brain is build up of a large number of domain specific programs, specialised
for solving different adaptive problems, the contemporary activation of many
of those sub-modules can give rise to conflicts and interferences. Those conflicts
and interferences represent, by themselves, an adaptive problem. This problem
is solved, in an evolutionary sense, by equipping the mind by super ordinate
programs that coordinate the all the adaptive modules into the correct response.
The reader
can refer to the original papers, and their references for a most complete
description of the E.P. approach to emotions.
Our model is based on a complete different approach, where emotions are considered as the expressions of oldest knowledge systems. An obvious reason for making this choice is the dominance of the evolutionary oldest structures of the brain in determination of emotional responses [3]. It would be somehow surprising, particularly from the point of view of E.P., to accept the idea that super ordinate coordination programs are located in the most ancient area of the brain. Apart that, it is evident that emotions, as commonly understood, are decision taking tools, similar to all other cognitive tools. In this sense a dichotomy is somehow an artificial move.
From our point of view emotions represent the trace of a knowledge system that has been very efficient in the past and that has given to the living beings that used it a gigantic evolutionary advantage. On the other hand, conflicts of emotions are a quite common experience in our lives and in animal experiments. Therefore the interpretation of emotions by E. P. would lead to need for super-emotions to solve emotional conflicts. This, on the other hand, is a well-known general problem, characterising all theories where a higher-level coordination super-agent is preferred to internal synergetic coordination of independent agents [4].
So emotions
are, in our concept, a very precise form of competent knowledge of the external
world, which coexists with other forms that intervened in successive stages
of the evolution, at least in mammals [3].
It is well
known however that areas of the most recently developed parts of the brain
are actively involved in the emotions-associated activities [5,6]. This observations
could, at least in principle, lead to serious criticism to our thesis. Actually
they totally fit our model.
In facts, if one considers the problem of the local, in time, evolution of the knowledge system of evolving beings, he/she obviously notices that, while improving its competence, it must retain its previous competence while slowly organising its innovations. At the same time, the new appearing competences must, to be supported by evolutionary mechanism, to give a competitive advantage to their carrier. In their initial state, this implies that they should act as a support to the older knowledge system. The idea, in a quite different form, was suggested in times by Baldwin [8].
These observations imply that there must exist some form of coordination between the pre-existing and the new module in the first stage of growth of the latter. This is, as discussed above, needed to understand the initial competitive advantage made available by the new module.
The need for some emotional super-program by E.P. is somehow the consequence of the assumption that the brain is the sum of specialized neural circuits solving different adaptive problems [2]. The implication on the mind concept is that it consists of different autonomous functionally specialized units, which are considered as almost isolated dedicated mini-computers.
We believe that there exist sufficient evidences to maintain that the vision of a mind represented by the sum of specialised modules is just a zero approximation description, which, while capturing some important features of the problem, represents a somehow too simplistic model. We also believe that this vision has lead to the artificial need for coordination modules, as emotions.
In our vision, based on the fact that each brain module has an informational input and produces some output, a new emerging module represents an evolutionary attempt to improve the competence of the living being. Its support must necessarily be interpretable as a refining of the previous information crunching in view of an improvement of the survival probability of the living beings. Simplifying somehow the discussion to make our vision clear, we concentrate on a very clear-cut environmental situation. Assume that a certain external state of affairs implies a survival risk for the living system and that the already existing knowledge module is capable to identify it and produce a competent primitive reaction. Such a reaction represents a useful competence. Why should we call it primitive? This judgement refers necessarily to an external, omniscient observer, who could judge the reaction from the exterior. Such an observer could for example “observe” that the reaction is too expensive from the energetic point of view and would give rise in the future to negative consequence. In any case, the observer would conclude that, if the living beings had been able to take into proper account other information, it would have adopted a more appropriate choice. This is why the observer would have called the reaction “competent, but primitive”.
Consider now a complete different situation which we could define a neutral one. There are no risks around; no food is immediately available at a reasonable distance. Correctly the primitive living being is quietly swimming around at a low speed. The observer could decide, on the basis of his anatomical and physiological observations that the being is primitive, not that its reactions are primitive.
Even from the point of view of the external observer, in the first dangerous situation considered above, the identification of the risk by the simple system was correct. His judgement of primitivism would involve the reaction rather. So the problem sits in the reaction, not in the judgement implicitly attributed to the primitive being.
This leads to the following interesting question: “why should the primitive being give up with its implicit judgement that was considered correct also by an omniscient external observer?” Of course we can translate the previous quite rhetoric question into a more pragmatic statement: there are no evolutionary reasons to modify or cancel the neuronal module that has produced a correct classification of a dangerous state of affairs, while there exist excellent evolutionary reasons to improve its reaction to such a state of affairs.
The simple system’s evolutionary problems are the following: to improve its information collection and analysis while retaining the neuronal module that has produced the correct implicit judgements of dangerous situations. The modification of such a module would imply a catastrophic risk consisting of misjudgements of a number of dangerous situations while the updating is going on. It is therefore evolutionary erroneous (we do not mean it is impossible, but simply that it has a very low probability of success). In simple words, there seem to us that there exist a number of very precise reasons to conclude that next modules will be evolutionary advantageous as far as they will be able to support the simple system to solve its evolutionary problems as clarified above. We sum up the characteristics of the new module activity to optimise the evolutionary advantages:
1) to avoid the loss of the implicit correct judgement of the older module, the newer one must receive its alarm message.
2) it must access to more detailed information about the environment
3) it must decompose the original environment analysis carried out by the old module into a class of relevant differentiated situations, capable of giving rise to more appropriate reactions
4) it must be capable of affecting the oldest module output effect on reaction without modifying its information process
5) it must be capable of leaving the reaction decision when it can not contribute significantly to the improvement of the competence.
We consider
the emotions as the expression of the oldest modules that appeared during
the brain evolution, following the above model. Our concept, developed here
in terms of information and algorithmic complexity theory, leads to a vision
of emotions definetily diverging from that of evolutionary psychology.