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2Problem Solving from an Evolutionary



Gestalt psychologists approach towards problem solving was a perceptual one. That is, for them, the questions about problem solving were:

• how is a problem represented in a persons mind, and

• how does solving this problem involve a reorganisation or restructuring of this representation?

Restructuring is basically the process of arriving at a new understanding of a problem situation -changing from one representation of a problem to a (very) different one. The following story illustrates this:

Two boys of different age are playing badminton. The older one is a more skilled player, and therefore it is predictable for the outcome of usual matches who will be the winner. After some time and several defeats the younger boy finally loses interest in playing, and the older boy faces a problem.

The usual suggestions, according to M. Wertheimer (1945/82), at this point of the story range from 'offering candy' and 'playing another game' to ' not playing to full ability' and 'shaming the younger boy into playing'. And this is what the older boy comes up with:

He proposes that they should try to keep the bird in play as long as possible - and thus changing from a game of competition to one of cooperation. They'd start with easy shots and make them harder as their success increases, counting the number of consecutive hits. The proposal is happily accepted and the game is on again.


There are two very different ways of approaching a goal-oriented situation. In one an organism readily reproduces the response to the given problem from past experience. This is called reproductive thinking.

The second way requires something new and different to achieve the goal, prior learning is of little help here. Such productive thinking is (sometimes) argued to involve insight. Gestalt psychologists even state that insight problems are a separate category of problems in their own right.

Tasks that might involve insight usually have certain features - they require something new and nonobvious to be done and in most cases they are difficult enough to prevent that the initial solution attempt is successful. When solving this kind of problems one experiences a so called "AHA-experience" - the solution pops up all of the sudden. At one time they do not have the answer to a problem and in the next second it's solved.

Problem Solving from an Evolutionary Perspective


Sometimes, previous experience or familiarity can even make problem solving more difficult. In effect habitual directions can get in the way of finding new directions. This is called fixation.

Mental Fixedness

One approach to studying fixation was study wrong-answer verbal insight problems. To this, people tend to give rather an incorrect answer when failing to solve, than to give no answer at all. A typical example is, when people are told that, on a lake, the area covered by water lilies doubles every 24 hours and that it takes 60 days to cover the whole lake, and are asked: 'How many days does it take to cover half the lake?' the typical respond is '30 days' (whereas 59 days is correct).

These wrong solutions are due to an inaccurate interpretation, hence representation, of the problem. This can happen because of 'sloppiness' (a quick shallow reading of the problem and/or weak monitoring their efforts made to come to a solution). In this case error feedback should help people to reconsider the problem features, note the inadequacy of their first answer, and find the correct solution. If, however, people are truly fixated on their incorrect representation, being told the answer is wrong doesn't help. In a study made by P.I. Dallop and R.L. Dominowski in 1992 these two possibilities were contrasted. In approximately one-third of the time error feedback led to right answers, so only approximately one-third of the wrong answers were due to inadequate monitoring.

Functional Fixedness

Functional fixedness concerns the solution of object-use problems. The basic idea is that, when the usual way of using an object is emphasized, it will be far more difficult for a person to use that object in a novel manner.

Problem Solving - Modern Approaches

Problem Solving as a Search Problem

The idea of regarding to problem solving as search problems was invented by Alan Newell and Herbert Simon while trying to design computer programs which could solve certain problems. This led them to develop a program called General Problem Solver which was able to solve any well-defined problem that can be formalized like chess or the towers of hanoi, but was not able to solve any real world problem.

Any given problem consists of two special states namely an initial and a desired final or goal state. To represent all possible situations between the initial and the goal state, intermediate states were introduced. Additionally there exist a set of operators to move from one state to another. A solution is a sequence of actions describing how to reach the goal state. The simplest method to solve a problem, defined in these terms, is to search for a solution by just trying one possibility after another (also called trial and error).

As already mentioned, this method of problem solving is not capable of solving real world problems since it is usually not possible to formalize these problems in such a way that a search

Chapter 2

algorithm is able to search for a solution.

Means-End Analysis

Another way is to try to divide a problem into smaller ones by creating sub goals. This method is called means-end analysis and can be best demonstrated with the towers of hanoi problem. The initial state is a stack of discs of different sizes on a peg. There are three pegs (A, B and C) and the discs are on the left one. A disc has to be always placed on a bigger one or on an empty peg. The goal is to move the stack of disks to the right peg, but only one disc can be moved at once. The following recursive algorithm solves this problem by using the means-end analysis:

1. move n-1 discs from A to C

2. move disc #n from A to B

3. move n-1 discs from C to B

(n is the total number of discs)

With each recursive loop the problem is reduced by one.

This is an important everyday problem solving strategy - like, say, writing this chapter of the book. We describe one aspect after another to give you, the reader, an overview of the subject that is as comprehensible as possible.


Analogies describe similar structures and interconnect them to clarify and explain certain relations. In a recent study, for example, a song that got stuck in your head is compared to an itching of the brain that can only be scratched by repeating the song over and over again.

Restructuring by Using Analogies

One special kind of restructuring, the way already mentioned during the discussion of the Gestalt approach, is analogical problem solving. Here, to find a solution to one problem - the so called target problem, an analogous solution to another problem - the source problem, is presented.

An example for this kind of strategy is the radiation problem posed by K. Duncker in 1945:

As a doctor you have to treat a patient with a malignant, inoperable tumor, buried deep inside the body. There exists a special kind of ray, which is perfectly harmless at a low intensity, but at the sufficient high intensity is able to destroy the tumor - as well as the healthy tissue on his way to it. What can be done to avoid the latter?

When this question was asked to participants in an experiment, most of them couldn't come up with the appropriate answer to the problem. Then they were told a story that went something like this:

A General wanted to capture his enemy's fortress. He gathered a large army to launch a full-scale
direct attack, but then learned, that all the roads leading directly towards the fortress were blocked by mines. These roadblocks were designed in such a way, that it was possible for small groups of the fortress-owner's men to pass them safely, but every large group of men would initially set them off. Now the General figured out the following plan: He divided his troops into several smaller groups and made each of them march down a different road, timed in such a way, that the entire army would reunite exactly when reaching the fortress and could hit with full strength.

Here, the story about the General is the source problem, and the radiation problem is the target problem. The fortress is analogous to the tumor and the big army corresponds to the highly intensive ray. Consequently a small group of soldiers represents a ray at low intensity. The solution to the problem is to split the ray up, as the general did with his army, and send the now harmless rays towards the tumor from different angles in such a way that they all meet when reaching it. No healthy tissue is damaged but the tumor itself gets destroyed by the ray at its full intensity.

M. Gick and K. Holyoak presented Duncker's radiation problem to a group of participants in 1980 and 1983. Only 10 percent of them were able to solve the problem right away, 30 percent could solve it when they read the story of the general before. After given an additional hint - to use the story as help -75 percent of them solved the problem.

With this results, Gick and Holyoak concluded, that analogical problem solving depends on three steps:

1. Noticing that an analogical connection exists between the source and the target problem.

2. Mapping corresponding parts of the two problems onto each other (fortress → tumor, army → ray, etc.)

3. Applying the mapping to generate a parallel solution to the target problem (using little groups of soldiers approaching from different directions → sending several weaker rays from different directions)

Next, Gick and Holyoak started looking for factors that could be helpful for the noticing and the mapping parts, for example:

Discovering the basic linking concept behind the source and the target problem.


This basic linking concept (see above) was called problem schema.

To activate a schema, schema induction is necessary.

One successful way to achieve schema induction by Gick and Holyoak: Before letting the participants solve the radiation problem the instructor gave them two stories to read, the one with the General and one with a similar outline. Now the participants were asked to write a brief summary about the similarities of these stories.

When the underlining similarities where indirectly emphasized in this way, 52 percent of the participants were able to solve the radiation problem without any hints given.

How do Experts Solve Problems?

With the term expert we describe someone who devotes large amounts of his or her time and energy to one specific field of interest in which he, subsequently, reaches a certain level of mastery. It should not be of a surprise that experts tend to be better in solving problems in their field than novices (people who are beginners or not as well trained in a field as experts) are. They are faster in coming up with a solution and have a higher success rate of right solutions. But what is the difference between the ways experts and nonexperts solve problems? Research on the nature of expertise has come up with the following conclusions:

• Experts know more about their field,

• their knowledge is organized differently, and

• they spend more time with analyzing the problem.

When it comes to problems that are situated outside the experts' field, their performance often doesn't differ from that of novices.


An experiment by Chase and Simon (1973a, b) dealt with the question how well experts and novices are able to reproduce positions of chess pieces on chessboards, shown to them briefly. The results showed, that experts were far better in reproducing actual game positions, but that their performance was comparable with that of a novice when the chess pieces were arranged randomly on the board. Chase and Simon concluded, that the superiority on actual game positions was due to the ability to recognize them from the more or less 50,000 patterns stored in an expert's memory. In comparison, for a good player there may be 1,000 patterns and for a novice only few to none at all.


In 1982, M. Chi and her co-workers took a collection of 24 physics problems and presented them to a group of physics professors, as well as to a group of students with only one semester of physics. The task was to group the problems based on their similarities.

As it turned out, the students tended to group the problems based on their surface structure (similarities of objects used in the problem), whereas the professors used their deep structure (the general physical principles) as criteria.


Experts often spend more time trying to understand the problem before actually trying to solve it. This way of approaching a problem may often result in what appears to be a slow start, but in the long run this strategy is much more effective.

Divergent Thinking

The term divergent thinking describes a way of thinking that doesn't lead to one goal, but is open -ended. Problems that are solved this way can have a large number of potential 'solutions' of which none is exactly 'right' or 'wrong', though some might be more suitable than others. It can be contrasted by convergent thinking - thinking that seeks to find the correct answer to a specific problem.

Divergent thinking is often associated with creativity, and it undoubtedly leads to many creative ideas. Nevertheless, researches showed that in the processes that result in original and practical inventions, things like searching for solutions, being aware of structures, and looking for analogies are also heavily involved.

The Evolutionary Perspective

In 1831 Charles Darwin began to develop the evolutionary theory which was meant to explain why there are so many different kinds of species. This theory also is important for psychology because it explains how species were designed through evolution and what their goals are. By knowing the goals of species it is possible to explain and predict behaviour.

Natural Selection

The mechanism of natural selection is the basic and most important one of which were introduced by the theory of evolution. It is this process that makes organisms with superior traits more likely to survive and reproduce. Without natural selection the growth of populations is exponential. For example

an organism that reproduces once a day will create a population of about 229 organisms within a month. In natural populations this is not the case and most populations are relatively stable, since most organisms do not have as many offspring as they might have. This is caused by the environment. Hence, if an individual is better at finding food or avoiding predators it is more likely that it will survive. This ability which enables the individual to survive will be passed on to the next generation. On the other hand if an individual fails to survive its disadvantages will not be passed on to the next generation. Over many generations this natural selection will lead to individuals that are better adapted to their environment. This process may also be called "reproduction of the fittest". Natural selection can only work if there are random changes in the genetic process, also called mutations. Only if these mutations are significant, natural selection can choose which version better solves the problem of "staying in the game of evolution".

As traits can only spread through reproduction, natural selection is a very slow process. The time until an individual is able to reproduce is called the generation time (approx. 20 years for humans). Evolution is such a slow process since natural selection can only choose from existing alternatives. That is, until a new trait becomes common it has to develop and spread in the whole population which of course takes much time.

Adaptation As a Result of Natural Selection

Variations in individuals are constantly tested whether they help to survive in the environment or not. This variation can be of any kind, for example an enhancement of the body or a new behaviour that
enables the individual to solve certain problems which are necessary to survive or aids reproduction. These variations are called adaptations because they adapt the individual to its environment. Adaptations are structurally complex and support reproduction.

Psychological Adaptation

Evolutionary psychologists think of the mind as a modular system. This perspective on modularity was mainly developed by Leda Cosmides and John Tooby. It is based on the assumption that the mind has evolved by natural selection and therefore should solve the same problems as other organs namely survival and reproduction. Each module of our mind is responsible for one task (e.g. face recognition) and can be adapted by natural selection. So behaviour is not adapted directly but rather indirectly by modifying the underlying neuronal networks to produce adaptive behaviour.

Adaptations May Be Out-of-Date

A disadvantage of the slow evolutionary process is that when the environment changes quickly, adaptive functions and behaviour may be out-of-date. The result is that organisms are better adapted to the past and this is an important point if we think about human social behaviour and the development of cultures (see chapter Evolutionary Perspective on Social Cognitions for details).

Sexual Selection

Besides the theory of natural selection there is another one called the theory of sexual selection. It states that there is also a kind of selection between individuals of the same sex which leads to a development and spread of traits in males or females.

Sexual selection depends on the success of certain individuals over others of the same sex, in relation to the propagation of the species; while natural selection depends on the success of both sexes, at all ages, in relation to the general conditions of life. —Charles Darwin, 1871

A famous example for sexual selection is the peacock. The evolution of its tail cannot be explained by natural selection only because it is neither very helpful to find food) nor does it help to avoid predators, even the opposite is the case. But it makes the peacock more attractive to the opposite sex and therefore conducts to reproduction due to the fact that this oversized tail can only be worn by a male that is strong enough to wear a disadvantage.


Natural selection favours the strong and selfish who! acts in his own interest. But there are other traits likel

altruism which are very common in human behaviour and it Darwin argued that the female peahen chose to seems that they cannot be explained by natural selection mate with the male peacock who had the most

only. With regard to a whole group traits can be beautiful plumage in her mind (intersexual


characterized as

• increasing the fitness of the individual (self) or

• increasing the fitness of the group.

Altruism obviously increases the fitness of the group, but decreases the fitness of individuals what at first glance conflicts with the theory of evolution and natural selection. But there are three attempts to explain why individuals decrease their fitness for the fitness of a group, namely

1. group selection,

2. kin selection and

3. reciprocal behaviour

which will be explained in more detail in chapter Evolutionary Perspective on Social Cognitions. We will focus here on reciprocal behaviour with regard to problem solving.

Reciprocal Behaviour

Why should an individual behave altruistic if it cannot be sure whether its recipient will also behave altruistic or not? Reciprocity is one explanation for these phenomena. That is, an altruistic individual will only offer an altruistic act to an individual which is known to be altruistic and will withhold altruistic behaviour to individuals which only act selfish. This exception prevents altruists from extinction and allows them to spread in population, but it presupposes that both individuals interact more than once and that they are able to recognize each other.

We can distinguish two types of reciprocal behaviour: direct and indirect reciprocity. The direct one is an exchange of altruistic behaviour between the same two individuals ("I scratch your back and you'll scratch mine") whereas the indirect one is between different individuals ("I scratch your back and someone will scratch mine"). The latter is even more complicated to explain, but it is a fundamental trait in our contemporary society. The basic idea to explain these phenomena is the development of reputation in society. That is, altruists decide whether or not to interact with someone according to the reputation of an individual.

(Iterative) Prisoner's Dilemma

The problem of cooperation is also topic in game theory a branch of applied mathematics where players try to maximize their winnings. There are many convergences between the theory of reciprocity and game theory, one famous example is the prisoner's dilemma. Two people A and B have been captured by the police, they committed a crime but the police is not able to proof that they are guilty, but they have enough evidence to arrest them for six months. Before A and B have been captured by the police they both agreed to keep silent. At the police department they were questioned in separate rooms and both have the choice to cooperate with his partner or with the police. If one betrays the other he will get free and his partner will have to serve for ten years. If they both betray each other they will both have to serve for two years. But if both keep silent, they only have to serve for six months.

Prisoner B

Stays Silent


Prisoner A serves ten

Stays Silent

Both serve six months



Prisoner B goes free


Prisoner A goes free


Prisoner B serves ten years

Both serve two years

The dilemma is that both accused people do not know how the other has decided or will decide. Regardless how the other will decide, confessing the crime will improve the outcome. If A betrays B, A will get free or he will stay in prison for two years. If he does not betray B, A will stay in prison for six months or ten years depending on however B decides. So obviously the best choice is to betray the other. There is an interesting extension of the dilemma called iterative prisoner's dilemma. The game is played again and again so it is possible to punish selfish behaviour in order to support altruism. One good strategy for the iterative prisoner's dilemma is tit-for-tat. At the first round this strategy suggests to cooperate with the partner. All other rounds one will do whatever the partner did in the round before. If someone betrays his partner, he will get punished next round. On the other hand, if someone always acts altruistic he will get paid back. This strategy is nothing but reciprocity.


When bringing Problem Solving and evolution together, explaining consciousness is an important point to understand how we have come this far. The answer shall be given in three steps: (1) The advantages that consciousness gave us during the evolutionary process. (2) The observations, through which neuropsychology has approached consciousness. Observations of various kinds of impairment like blindsight, commissurotomy, hemineglect, anosognosia, and also another approach called “binding problem” which tries to explain how distributed activities of neurons make up conscious perception by means of EEG monitoring. (3) Finally, what is probably the most controversial step, dealing with some suggestions of how consciousness is involved in Problem Solving, namely (psycho-)functionalism, metacognition and situation models.

Evolution of Consciousness

When trying to explain consciousness from an evolutionary perspective, there are two possible options of approach. Either you specify the function of consciousness and thus give reasons for an evolutionary progress or you explain how our abilities we gained through evolution made it inevitable to make us conscious. Furthermore, it has to be considered at what time consciousness may have appeared, that is where we can find consciousness in animals. While the first two theories presented here will give reasons for why the function of consciousness has some benefits, the third theory is more about the development of the brain that was not caused by any benefits of cognition but nevertheless enabled the emergence of consciousness.

(direct source [1])

As a pioneer in this field, William James (1890)[2] argued that evolution pushes the behaviour of an organism into a direction that is of interest for it. The brain was seen as an instrument to make predictions and therefore also having the ability to choose among many possibilities. So consciousness
is involved in reinforcing the favourable possibilities while repressing the unfavourable. James assumes that the evolution of consciousness happened at the same time at which the cerebrum had evolved. It allowed to selectively guide the nervous system in an environment that became more and more complex throughout evolution (1890/1891, p. 147)[2].

James distinguishes three classes of animal consciousness. The first class contains bilateral invertebrates (earthworms, leeches, spiders, and insects) that show a centralisation of the nervous system. The main criterion for this class is the differentiation between having a sensation and not having that particular sensation. Although this can only be considered as a primitive mental state, the detection of stimuli is thought to be a condition for consciousness. An example of scientific investigation was done by Keunzi and Carew (1991)[3] showing that the marine snail Aplysia californica reacted differently to light from various directions and could also be trained to behave in a certain way through conditioning.

The second class contains animals that do not only remember previous experiences but are also capable of equate them with present experiences. They are able to copy a model or in other words imitate a behaviour which is regarded as the beginning of conceptual thought. Here the animal class of cephalopods should be mentioned. Octopus vulgaris which belongs to this class was examined by Fiorito and Scotto (1992)[4]. They separated the octopuses into the “demonstrator” and “observer” group. The “demonstrator” group was trained with conditioning techniques to attack either a white or a red ball when offered both. Then an octopus of the “observer” group watched an octopus from the “demonstrator” group attacking a ball with the specific colour. The “observers” imitated the attacking behaviour rapidly, however they sometimes chose the ball with the respective other colour. Because of this choice, it is assumed that a primitive form of consciousness is involved.

The third class entails humans as well as great-apes (gorillas, orang-utans, chimpanzees) and cetaceans (whales, dolphins). In comparison to other animals they all possess a larger surface area of the cerebrum, the neocortex. The main feature of this class is the capability of self-consciousness which is according to James a more complex form. Gallup (1970)[5] introduced an experiment to find out whether animals or infants are able to distinguish “me” from “not me”. Red dye is put on the forehead that can not be recognized except with the aid of a mirror. However, it is in question whether this method can be seen as a test for self-consciousness in the sense that there is an awareness of one's own thoughts.

These three classes were shortly presented because later, in the third part of the subtopic of consciousness, we will introduce a general definition for consciousness which will give us a different but quite similar classification and a suggestion of how to overcome this last problem.

(Blackmore, S. J., 2004 [6])

Another theory that contributes to the idea of consciousness having a function is held by Nicholas Humphrey. The main thesis is that consciousness has a social function. While animals like chimpanzees live in a social environment, humans are highly specialized to social skills. Humphrey believes that skills like understanding, predicting and manipulating the behaviour of others became necessary for our ancestors because, in a group, they were facing situations like deciding whether a group member is a friend or an enemy or when they should form alliances etc. He calls our ancestors having evolved this way “natural scientists”.

How consciousness could have had influenced this can be shown by considering the following
scenario. Imagine an early hominid Suzy seeing Mick with a large piece of food, with him sits her friend Sally. Suzy thinks about distracting Mick so that Sally could grab the food. But first she needs to ask herself various questions like “Is Sally going to share the food with her”. In other words, she needs to put herself into the position of another person. Thus our ancestors developed a self-reflexive insight or an “inner eye” that gives us a perception like other sense organs, however, not of the outer world but of one's own brain activities (1986[7]; 2002[8]). According to this theory consciousness can be attributed to social creatures like great-apes, elephants, wolves and dolphins. But it would also claim that most creatures are not conscious.

The third theory which gains support from Robert Ornstein (1991)[9] is mainly about the necessity to withstand heat mainly for purposes of our head which means that the growth of the brain about 2 million years ago was caused neither by social nor cultural but physiological adaptation. The reason for this assumption is that the increasing size of the brain happened in advance of human characteristics.

First, the importance of cooling the head shall be emphasized. Human beings are sensitive to high temperatures because a rise of 1 or 2ºC above normal can disturb brain functions and a rise of 4ºC can cause a heat stroke. In addition, human beings lack a cooling system like dogs for example, they have a special blood circuitry which cools the blood when they start panting. One way to achieve cooling is an upright posture. It is assumed that bipedalism was influenced by a climate change that due to its dry conditions thinned the forests. Thus, hunting became a more reliable source for food than plants. But it also caused the temperature to rise in our body. An upright posture had the effect that at noon the sun hit a much smaller surface and more of our body mass is above the hot ground that had a vegetation of 50 cm (adopted from Peter Wheeler). After this evolutionary step it took about one million years until the brain started to grow. Anthropologist Dean Falk assumes that during this time our ancestors developed the net of emissary veins that lead in and out of the brain. In normal circulation these veins carry heated blood from the brain out to the surface of the skull in order to cool it down. If the brain temperature rises due to exercise like conditions, the blood flow in these veins reverses.

The second method our ancestors developed to withstand heat is increasing the cortical size (Konrad Fialkowski, 1986)[10]. On the one hand this enhances the cooling effect of the emissary veins mentioned before. On the other hand the abundance of neurons made it possible that other areas of the brain could take over tasks when there was a loss of neurons. An indication for such a development is that a small piece of the cortex looks like any other piece and except for the size it is even similar to that of other species. Also the density of the neurons is almost the same as for example in chimpanzees. This development could explain how the human brain gained a parallel organization which is preliminary for complex thought. The oversupply of supporting cells (glia) might have allowed more interconnections between neurons due to the space they fill up.

Compared to the previous theories consciousness has no function but is a result of the evolution of the brain. It is important to see that evolution as such is independent of intellect. We will come back to this later in part three because this hint is essential for the definition of consciousness and will be discussed in the short remarks on functionalism.

Neuropsychology and Consciousness

In philosophy there are many notions of consciousness. The topics of the second part are most likely ascribed to phenomenal consciousness which is about our subjective experiences. However, philosophers like John Searle and Thomas Nagel list three features of consciousness that seem to be essential: subjectivity, unity and intentionality. First we will deal with unity also referred to as the
“binding problem”.

The model of Wolf Singer[11] tries to explain the binding problem with a concept other than the classical one. The classical concept says that cognitive operation is the generation of explicit neuronal representations. These representations are realized by individual neurons that are tuned to particular constellations of input activity. Specificity is gained through selective convergence of input connections in hierarchically structured feed-forward architectures. But according to Singer this view has several disadvantages. It requires a high number of neurons and seems to be inappropriate for the encoding of syntactical structure and hierarchical relations of elements composed in a perceived object (Roelfsema, P.R., Engel, A.K., Koenig, P. & W. Singer, 1996)[12].

So the concept suggested by Singer is a distributed dynamical process which relies on self-organization. It is assumed that neurons are associated with so called functionally coherent assemblies that represent objects. The advantage is that one neuron can participate in different assemblies. Each neuron is tuned only to a subset of elementary features (colour, movement, orientation). This concept may be strong enough to explain phenomenal consciousness due to the combinatorial complexity and flexibility. In contrast single neurons show little difference in sleeping or anesthetized animals.

Now two important questions arise. What is the mechanism of selection that dynamically separates one assembly into two and how is an assembly labelled in order to be recognized by subsequent processes. To give an answer to the first question there are three possibilities. First, the inhibition of non-grouped responses, second, the selected response can be amplified and third, the selected cells fire in synchrony. However, it is unlikely that the modulation of discharge rates (action potential) is involved for the following reasons. An explanation of this type leads to ambiguities when considering the second question of how neurons are labelled. In addition, the processing time would be too high because for evaluation the action potentials first need to be integrated. Also different assemblies can not co-exist in time if they share the same neurons. Otherwise they would not be indistinguishable. This would only allow a sequential processing.

The main hypothesis is that selection and labelling is achieved through the synchronization which comes in with several advantages. It is independent of the firing rate of single neurons and can be used in parallel. Assemblies can follow one another much faster (Singer, 1999/2000)[13] and output activity has a high precision because of minimal latency jitter (Abeles, M. 1982[14]; Softky, W. 1994[15]; Koenig, P., A.K. Engel & W. Singer, 1996[16]). The processing speed increases because synchronized EPSPs trigger action potentials with a minimal delay.

With this hypothesis some preliminaries for selection have to be considered. Neurons must be sensible to detect coincident synaptic input. Further, they have to be able to coordinate rapidly in a context dependent way. One example of neurons working with high precision is the auditory nucleus where delays in the sub millisecond range are evaluated. Another example is the oscillatory responses of retinal ganglion cells which are transmitted to cortical neurons (Castelo-Branco, M., S. Neuenschwander & W. Singer, 1998)[17]. When awake these oscillatory patterns are in the gamma frequency range of 30-60 Hz (also see Crick, F. & Koch, C., 1990)[18]. In many experiments rapid synchronization has been observed in the visual cortex of cats. Fluctuations of the local field potential shifted the response latency accordingly to the polarization of the potential. In other words, these sub threshold oscillations can cause a delay in the response and thus are responsible for synchronization tasks.

Coming back to the binding problem, we can examine it with the study of attention. Attention can
facilitate synchronization. In one experiment cats were trained to react to visual stimuli with a motor response. When they focused their attention, cortical areas that are involved in the execution of the task synchronized their activity. Immediately after the stimulus was shown, synchronization further increased. Thus, attention has the functional role of expectancy. It acts like a dynamic filter which in advance selects neurons that participate in the execution and therefore accomplishes binding.

Now we will have a look an various brain damages which reveal additional insights in the subject of consciousness.


Lawrence Weiskrantz (1986[19]; 1997[20]) had been studying a patient called D.B. who lost vision in a large part of his left visual field due to the removal of a tumor that was in an area of his visual cortex. In an experiment a circle containing stripes was shown to him in the blind field. He said that he could not see anything within this area, for he was blind there. However, when he was asked to guess whether the orientation of the stripes is either vertical or horizontal, he answers correctly in 90-95 % of the time. (compare with hemineglect below)

Commissurotomy (split-brain)[6]

In the 1960s operations severing the corpus callosum had been carried out. This should prevent epileptic seizures spreading from one hemisphere to the other as the corpus callosum is the primary root where both hemispheres can interact. When the patients recovered they performed equally well on problem solving tasks and language as before. When considering the visual pathway, a cut through the corpus callosum prevents information from going from one side to the other (see picture). This affects paths that start from the nasal side. So one hemisphere will only receive information from the contralateral side of the visual field (here: left hemisphere only blue path, right hemisphere only red path).

Patient P.S. was shown a snow scene on the left side (right hemisphere) and a chicken claw on the right side (left hemisphere). Because the right hemisphere controls the left side of the body, he pointed to a shovel with the left hand and to a chicken with the right hand. When he was asked why, he said, “The chicken claw goes with the chicken, and you need a shovel to clean out the chicken shed” (after Gazzaniga & LeDoux, 1992). Other experiments show that this confabulation is common. No patient would admit that they have a split brain but invent a story that seems plausible to their reaction.


Patients that suffer from hemineglect ignore or pay no attention to the side of space contralateral to the lesion. For example when asked to copy a picture of a clock, they may only be able to draw the right half which in this case would be caused by a lesion in the right hemisphere. Hemineglect occurs within different frames which means that the symptom occurs with regard to the horizontal plan (left-right) or the vertical plane (top-bottom) or to non spacial frameworks which can be object based (e.g. words).

Each hemisphere seems to have an attentional bias on the contralateral side. This can be seen when you compare a chimeric picture containing a face that has a smile on the left side with the same picture
mirrored. If you are right-handed which means that your emotional interpretation is better in the right hemisphere, you will perceive the first picture as being happier (Levy, J., Heller, W., Banich, M.T. & Burton, L.A., 1983)[22]. Another property is that lesion in the right hemisphere are more severe causing patients to slow on response time. In an experiment (Weintraub, S. & Mesulam, M. 1987)[23] where patience with left- and right-hemisphere damage and intact persons (control group) should mark items on a display, patients performed worse on the neglected hemispace respectively. However, patients with a right hemisphere lesion performed even worse than those with left hemisphere lesion. There are two possibilities to explain this. First, the attention bias is greater in the right hemisphere and second, the attention drops towards the ipsilateral side of each hemisphere while the right hemisphere does so with a higher gradient.

What is interesting is that patients still seem to process information of the neglected field. When patients were shown two pictures, the first presented 400 ms earlier in the neglected field, they responded faster if those pictures were related although they were not aware of the first one (Berti, A. & Rizzolatti, G., 1992)[24].


The unawareness of once disabilities is called anosognosia (Damasio, A., 1999[25]; Weiskrantz, L., 1997[20]). It occurs with the damage to particular parts of the right parietal lobe. For example patients who are unable to stand up still insist that they would be able to and at the same time make excuses that they cannot get out of bed. There are extreme cases like a blind patient told that he enjoyed watching TV (Sacks, O., 1992)[26].

Problem Solving and Consciousness

An explanation why consciousness plays an important role in the process of problem solving in itself leads to a problem because without a clear concept of consciousness one can always verify or deny its purpose. Therefore we will state a definition not claiming that it is correct but can be a ground of our discussion. It seems that such a definition presupposes that there is an objective description of a subjective experience. However, our approach assumes that consciousness is not the same as subjective experience and thereby explain consciousness without explaining why perception has a qualitative character. Nevertheless, we will also explain how sensations are related to consciousness.

To start up from the bottom, we will just ask whether a stone is conscious. Simply 'no' because stones are not alive. So what does life mean? Def.: Life is the part of the phenotype which is solely determined by the genotype excluding environmental influences on both phenotype and genotype (Mendel's law, mutation, genetic engineering). We can consciously change both and therefore we have to exclude them from definition. Otherwise we could not differentiate between life and consciousness. It does not mean that life cannot undergo an evolutionary process.

On the next level we have modalities which are experienced in a subjective way. The difference between creatures that are merely alive and creatures that can also perceive is that the former can only adapt through evolution whereas the latter can adapt during lifetime. An example for the first group is a virus while Aplysia californica would belong to the second group. The main idea is the ability to establish a representation of the environment. Through evolution these representations can gain an interpretative value for example the face of a tiger is interpreted as being dangerous (this idea goes back to Gerald Edelman). So we may conclude that sensations are representations plus their


How these

accomplished is


brain / neurons

representation / projection






interpretation. interpretations still unknown. ____,

evolution Finally, we will just define [

consciousness in a way we can deal

with it. Def.: Consciousness is the

ability to establish structured

sensations. The first notable property

would therefore be that

consciousness itself cannot be

perceived. If you imagine that it is a

structure, you might say it is

perceivable but this for itself is not

consciousness because it is just a

semantic content as described below.

So how do we understand this

structure. It can be thought of as an

axiomatic system where we can give

content a meaning, that is we know

what the world has to be like to

fulfill a sentence of this system (see S

Ludwig Wittgenstein). From this we (static view syntax dynamic view inference)

conclude that our sensationsConsciousness diagram (GFDL - Marc Heimann)

compose a semantic content

(binding). Unfortunately we would have to guess that this is learned during childhood. One example is

visual object recognition. We will show later that consciousness should not be defined over objects but,

as we already did, over sensations. Then we may conclude that we have the possibility to transcend

various systems because semantic and syntax are both realized on the sensational level. This allows us

to perform metacognitive tasks because we can switch syntax to the roll of semantic enabling us to

solve problems in a way that differs from evolution for it is done on a symbolic level. One example of

how this definition can be applied is linguistic. Linguistic shows that there are various levels of

processing like morphology, syntax, semantic, pragmatic. These levels altogether compose a system

that contributes all its aspects for evaluating the meaning of a sentence.


Defining consciousness as an ability to structure sensations, confabulation in this sense can be seen as its performance. People try to give something a meaning and it is important to see that they can do so despite the lack of information. Confabulation is a constructive process which can be performed without semantic content. Blindsight and hemineglect show that patients can perceive sensations (orientation, color, emotional expression). But they are unable to recognize objects which means that semantic content may not affect consciousness. Due to this double dissociation we can conclude that consciousness is independent of semantic content. Now we can say that problem solving may happen unconsciously for example when riding a bike. This can be accomplished due to plasticity (Kandel, E. R., Schwartz, J. H., Jessell, T. M., 2000)[27]. However, we suggest that consciousness must be involved when we face new problems. We will show examples where consciousness is useful and one example where it is inevitable.


We will consider two questions. The first is how cognition can have a function that is relevant for the evolutionary process. The evolutionary process has to be viewed very precisely. It does not act upon individuals but upon generations of individuals. Next, the genetic information of an individual is randomly chosen from its parents which means that there is no preference of any feature in the genetic code (Ornstein, R., 1991)[9]. If you imagine the evolutionary process as a tree, cognition virtually increases the branching factor because individuals having a lifetime adaption may better cope with environmental obstacles. Thus, cognition does not influence evolution but having cognition does. This leads us to the next question asking how functionalism would allow subjective experience when it actually states that on certain inputs there will be definite outputs. Indeed the answer is already given with the distinction of evolutionary adaption and lifetime adaption. The abilities of cognition with regard to the evolutionary process have nothing to do with the abilities of an individual to perceive.


1. ↑ Nielsen, M. (?) William James and the evolution of consciousness. La Trobe University. Retrieved May 20, 2006 from

2. ↑ 2.0 2.1 James, W. (1890/1981). The principles of psychology. Cambridge: Harvard University Press.

3. ↑ Keunzi, F. M., & Carew, T .J. (1991). Aplysia californica. Behavioral and Neural Biology, 55 (3), 338-355.

4. ↑ Fiorito, G., & Scotto, P. (1992). Observational learning in Octopus vulgaris. Science, 256, 545-547.

5. ↑ Gallup, G. G., Jr. (1970). Chimpanzees: Self-recognition. Science, 167, 341-343.

6. ↑ 6.0 6.1 6.2 6.3 Blackmore, S. J. (2004). Consciousness : An Introduction. New York: Oxford University Press.

7. ↑ Humphrey, N. (1986). The Inner Eye. London: Faber & Faber

8. ↑ Humphrey, N. (2002). The Mind made Flesh: Frontiers of Psychology and Evolution. Oxford: Oxford University Press.

9. ↑ 9.0 9.1 Ornstein, R. (1991). Evolution of Consciousness: The Origins of the Way We Think. New York: Simon & Schuster Paperbacks.

10. ↑ Fialkowski, K. (1986) A mechanism for the origin of the human brain: A hypothesis. Current Anthropology, 28, 540-43

11. ↑ Singer, W. (?) Consciousness and the Binding Problem. Max Planck Institute for Brain Research. Retrieved May 20, 2006 from

12. ↑ Roelfsema, P.R., Engel, A.K., Koenig, P. & W. Singer. 1996. The role of neuronal synchronization in response selection: a biologically plausible theory of structured representation in the visual cortex. J. Cogn. Neurosci. 8, 603-625.

13. ↑ Singer, W. 1999/2000. Response synchronization: A universal coding strategy for the definition of relations. In The New Cognitive Neurosciences, Second Edition. M.S. Gazzaniga, Ed.: 325-338. MIT-Press. Cambridge, MA.

14. ↑ Abeles, M. 1982. Role of the cortical neuron: integrator or coincidence detector? Isr. J. Med. Sci. 18, 83-92.

15. ↑ Softky, W. 1994. Sub-millisecond coincidence detection in active dendritic trees. Neuroscience 58, 13-41.

16. ↑ Koenig, P., A.K. Engel & W. Singer. 1996. Integrator or coincidence detector? The role of

Wikibooks | 23

Chapter 2

the cortical neuron revisited. Trends Neurosci. 19, 130-137.

17. ↑ Castelo-Branco, M., S. Neuenschwander & W. Singer. 1998. Synchronization of visual responses between the cortex, lateral geniculate nucleus, and retina in the anesthetized cat. J. Neurosci. 18, 6395-6410.

18. ↑ Crick, F & C. Koch, C. (1990) Towards a neurobiological theory of consciousness. Seminars in the Neurosciences, 2, 263-75

19. ↑ Weiskrantz, L. (1986) Blindsight: A Case Study and Implications. Oxford, Oxford University Press.

20. ↑ 20.0 20.1 Weiskrantz, L. (1997) Consciousness Lost and Found. Oxford, Oxford University Press.

21. ↑ Banich, M. T. (2004) Cognitive Neuroscience and Neuropsychology (2nd ed). Boston: Houghton Mifflin Company

22. ↑ Levy, J., Heller, W., Banich, M.T. & Burton, L.A. (1983) Asymmetry of perception in free viewing of chimeric faces. Brain and Cognition, 2, 404-419

23. ↑ Weintraub, S. & Mesulam, M. (1987). Right cerebral dominance in spatial attention. Archives of Neurology, 44, 621-625.

24. ↑ Berti, A. & Rizzolatti, G. (1992). Visual processing without awareness: Evidence from unilateral neglect. Journal of Cognitive Neuroscience, 4, 345-351.

25. ↑ Damasio, A. (1999) The Feeling of what happens: Body, Emotion and the making of Consciousness. London: Heinemann.

26. ↑ Sacks, O. (1992) the last hippie. New York Review of Books 39 (26 March), 51-60

27. ↑ Kandel, E. R., Schwartz, J. H., Jessell, T. M. (2000). Principles of Neural Science, 4th edition. New York: McGraw-Hill

• Carruthers, P. & Chamberlain, A. (2001). Evolution and the Human Mind: Modularity, Language and Meta-Cognition.

• Gaulin, S. J. C. & McBurney, D. (2000). Psychology: An Evolutionary Approach

• Goldstein, E. B. (2005). Cognitive Psychology: Connecting Mind, Research and Everyday Experience. Belmont: Thomson Wadsworth

• Held, C. & Knauff, M. & Vosgerau, G. (2006). Mental Models and the Mind: Current Developments in Cognitive Psychology, Neuroscience, and Philosophy of Mind (Advances in Psychology). Amsterdam: Elsevier B.V.

• Sternberg, R. J. & Davidson, J. E. (1996). The Nature of Insight.


• Evolution of Consciousness, by Olivia Moschetti

• Consciousness and the Binding Problem, by Prof. Dr. Wolf Singer

• Mental Models, by Philip N. Johnson-Laird

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