Category Archives: stages

Major conscious and unconcoscious processes in the brain: part 3: Robot minds

This article continues my series on major conscious and unconscious processes in the brain. In my last two posts I have talked about 8 major unconscious processes in the brain viz sensory, motor, learning , affective, cognitive (deliberative), modelling, communications and attentive systems. Today, I will not talk about brain in particular, but will approach the problem from a slightly different problem domain- that of modelling/implementing an artificial brain/ mind.

I am a computer scientist, so am vaguely aware of the varied approaches used to model/implement the brain. Many of these use computers , though not every approach assumes that the brain is a computer.

Before continuing I would briefly like to digress and link to one of my earlier posts regarding the different  traditions of psychological research in personality and how I think they fit an evolutionary stage model . That may serve as a background to the type of sweeping analysis and genralisation that I am going to do. To be fair it is also important to recall an Indian parable of how when asked to describe an elephant by a few blind man each described what he could lay his hands on and thus provided a partial and incorrect picture of the elephant. Some one who grabbed the tail, described it as snake-like and so forth.

With that in mind let us look at the major approaches to modelling/mplementing the brain/intelligence/mind. Also remember that I am most interested in unconscious brain processes till now and sincerely believe that all the unconscious processes can, and will be successfully implemented in machines.   I do not believe machines will become sentient (at least any time soon), but that question is for another day.

So, with due thanks to @wildcat2030, I came across this book today and could immediately see how the different major approaches to artificial robot brains are heavily influenced (and follow) the evolutionary first five stages and the first five unconscious processes in the brain.
The book in question is ‘Robot Brains: Circuits and Systems for Conscious Machines’ by Pentti O. Haikonen and although he is most interested in conscious machines I will restrict myself to intelligent but unconscious machines/robots.

The first chapter of the book (which has made to my reading list) is available at Wiley site in its entirety and I quote extensively from there:

Presently there are five main approaches to the modelling of cognition that could be used for the development of cognitive machines: the computational approach (artificial intelligence, AI), the artificial neural networks approach, the dynamical systems approach, the quantum approach and the cognitive approach. Neurobiological approaches exist, but these may be better suited for the eventual explanation of the workings of the biological brain.

The computational approach (also known as artificial intelligence, AI) towards thinking machines was initially worded by Turing (1950). A machine would be thinking if the results of the computation were indistinguishable from the results of human thinking. Later on Newell and Simon (1976) presented their Physical Symbol System Hypothesis, which maintained that general intelligent action can be achieved by a physical symbol system and that this system has all the necessary and sufficient means for this purpose. A physical symbol system was here the computer that operates with symbols (binary words) and attached rules that stipulate which symbols are to follow others. Newell and Simon believed that the computer would be able to reproduce human-like general intelligence, a feat that still remains to be seen. However, they realized that this hypothesis was only an empirical generalization and not a theorem that could be formally proven. Very little in the way of empirical proof for this hypothesis exists even today and in the 1970s the situation was not better. Therefore Newell and Simon pretended to see other kinds of proof that were in those days readily available. They proposed that the principal body of evidence for the symbol system hypothesis was negative evidence, namely the absence of specific competing hypotheses; how else could intelligent activity be accomplished by man or machine? However, the absence of evidence is by no means any evidence of absence. This kind of ‘proof by ignorance’ is too often available in large quantities, yet it is not a logically valid argument. Nevertheless, this issue has not yet been formally settled in one way or another. Today’s positive evidence is that it is possible to create world-class chess-playing programs and these can be called ‘artificial intelligence’. The negative evidence is that it appears to be next to impossible to create real general intelligence via preprogrammed commands and computations.

The original computational approach can be criticized for the lack of a cognitive foundation. Some recent approaches have tried to remedy this and consider systems that integrate the processes of perception, reaction, deliberation and reasoning (Franklin, 1995, 2003; Sloman, 2000). There is another argument against the computational view of the brain. It is known that the human brain is slow, yet it is possible to learn to play tennis and other activities that require instant responses. Computations take time. Tennis playing and the like would call for the fastest computers in existence. How could the slow brain manage this if it were to execute computations?

The artificial neural networks approach, also known as connectionism, had its beginnings in the early 1940s when McCulloch and Pitts (1943) proposed that the brain cells, neurons, could be modelled by a simple electronic circuit. This circuit would receive a number of signals, multiply their intensities by the so-called synaptic weight values and sum these modified values together. The circuit would give an output signal if the sum value exceeded a given threshold. It was realized that these artificial neurons could learn and execute basic logic operations if their synaptic weight values were adjusted properly. If these artificial neurons were realized as hardware circuits then no programs would be necessary and biologically plausible artificial replicas of the brain might be possible. Also, neural networks operate in parallel, doing many things simultaneously. Thus the overall operational speed could be fast even if the individual neurons were slow. However, problems with artificial neural learning led to complicated statistical learning algorithms, ones that could best be implemented as computer programs. Many of today’s artificial neural networks are statistical pattern recognition and classification circuits. Therefore they are rather removed from their original biologically inspired idea. Cognition is not mere classification and the human brain is hardly a computer that executes complicated synaptic weight-adjusting algorithms.

The human brain has some 10 to the power of 11 neurons and each neuron may have tens of thousands of synaptic inputs and input weights. Many artificial neural networks learn by tweaking the synaptic weight values against each other when thousands of training examples are presented. Where in the brain would reside the computing process that would execute synaptic weight adjusting algorithms? Where would these algorithms have come from? The evolutionary feasibility of these kinds of algorithms can be seriously doubted. Complicated algorithms do not evolve via trial and error either. Moreover, humans are able to learn with a few examples only, instead of having training sessions with thousands or hundreds of thousands of examples. It is obvious that the mainstream neural networks approach is not a very plausible candidate for machine cognition although the human brain is a neural network.

Dynamical systems were proposed as a model for cognition by Ashby (1952) already in the 1950s and have been developed further by contemporary researchers (for example Thelen and Smith, 1994; Gelder, 1998, 1999; Port, 2000; Wallace, 2005). According to this approach the brain is considered as a complex system with dynamical interactions with its environment. Gelder and Port (1995) define a dynamical system as a set of quantitative variables, which change simultaneously and interdependently over quantitative time in accordance with some set of equations. Obviously the brain is indeed a large system of neuron activity variables that change over time. Accordingly the brain can be modelled as a dynamical system if the neuron activity can be quantified and if a suitable set of, say, differential equations can be formulated. The dynamical hypothesis sees the brain as comparable to analog feedback control systems with continuous parameter values. No inner representations are assumed or even accepted. However, the dynamical systems approach seems to have problems in explaining phenomena like ‘inner speech’. A would-be designer of an artificial brain would find it difficult to see what kind of system dynamics would be necessary for a specific linguistically expressed thought. The dynamical systems approach has been criticized, for instance by Eliasmith (1996, 1997), who argues that the low dimensional systems of differential equations, which must rely on collective parameters, do not model cognition easily and the dynamicists have a difficult time keeping arbitrariness from permeating their models. Eliasmith laments that there seems to be no clear ways of justifying parameter settings, choosing equations, interpreting data or creating system boundaries. Furthermore, the collective parameter models make the interpretation of the dynamic system’s behaviour difficult, as it is not easy to see or determine the meaning of any particular parameter in the model. Obviously these issues would translate into engineering problems for a designer of dynamical systems.

The quantum approach maintains that the brain is ultimately governed by quantum processes, which execute nonalgorithmic computations or act as a mediator between the brain and an assumed more-or-less immaterial ‘self’ or even ‘conscious energy field’ (for example Herbert, 1993; Hameroff, 1994; Penrose, 1989; Eccles, 1994). The quantum approach is supposed to solve problems like the apparently nonalgorithmic nature of thought, free will, the coherence of conscious experience, telepathy, telekinesis, the immortality of the soul and others. From an engineering point of view even the most practical propositions of the quantum approach are presently highly impractical in terms of actual implementation. Then there are some proposals that are hardly distinguishable from wishful fabrications of fairy tales. Here the quantum approach is not pursued.

The cognitive approach maintains that conscious machines can be built because one example already exists, namely the human brain. Therefore a cognitive machine should emulate the cognitive processes of the brain and mind, instead of merely trying to reproduce the results of the thinking processes. Accordingly the results of neurosciences and cognitive psychology should be evaluated and implemented in the design if deemed essential. However, this approach does not necessarily involve the simulation or emulation of the biological neuron as such, instead, what is to be produced is the abstracted information processing function of the neuron.

A cognitive machine would be an embodied physical entity that would interact with the environment. Cognitive robots would be obvious applications of machine cognition and there have been some early attempts towards that direction. Holland seeks to provide robots with some kind of consciousness via internal models (Holland and Goodman, 2003; Holland, 2004). Kawamura has been developing a cognitive robot with a sense of self (Kawamura, 2005; Kawamura et al., 2005). There are also others. Grand presents an experimentalist’s approach towards cognitive robots in his book (Grand, 2003).

A cognitive machine would be a complete system with processes like perception, attention, inner speech, imagination, emotions as well as pain and pleasure. Various technical approaches can be envisioned, namely indirect ones with programs, hybrid systems that combine programs and neural networks, and direct ones that are based on dedicated neural cognitive architectures. The operation of these dedicated neural cognitive architectures would combine neural, symbolic and dynamic elements.

However, the neural elements here would not be those of the traditional neural networks; no statistical learning with thousands of examples would be implied, no backpropagation or other weight-adjusting algorithms are used. Instead the networks would be associative in a way that allows the symbolic use of the neural signal arrays (vectors). The ‘symbolic’ here does not refer to the meaning-free symbol manipulation system of AI; instead it refers to the human way of using symbols with meanings. It is assumed that these cognitive machines would eventually be conscious, or at least they would reproduce most of the folk psychology hallmarks of consciousness (Haikonen, 2003a, 2005a). The engineering aspects of the direct cognitive approach are pursued in this book.

Now to me these computational approaches are all unidimensional-

  1. The computational approach is suited for symbol-manipulation and information-represntation and might give good results when used in systems that have mostly ‘sensory’ features like forming a mental represntation of external world, a chess game etc. Here something (stimuli from world) is represented as something else (an internal symbolic represntation).
  2. The Dynamical Systems approach is guided by interactions with the environment and the principles of feedback control systems and also is prone to ‘arbitrariness’ or ‘randomness’. It is perfectly suited to implement the ‘motor system‘ of brain as one of the common features is apparent unpredictability (volition) despite being deterministic (chaos theory) .
  3. The Neural networks or connectionsim is well suited for implementing the ‘learning system’ of the brain and we can very well see that the best neural network based systems are those that can categorize and classify things just like ‘the learning system’ of the brain does.
  4. The quantum approach to brain, I haven’t studied enough to comment on, but the action-tendencies of ‘affective system’ seem all too similar to the superimposed,simultaneous states that exits in a wave function before it is collapsed. Being in an affective state just means having a set of many possible related and relevant actions simultaneously activated and then perhaps one of that decided upon somehow and actualized. I’m sure that if we could ever model emotion in machine sit would have to use quantum principles of wave functions, entanglemnets etc.
  5. The cognitive approach, again I haven’t go a hang of yet, but it seems that the proposal is to build some design into the machine that is based on actual brain and mind implemntations. Embodiment seems important and so does emulating the information processing functions of neurons. I would stick my neck out and predict that whatever this cognitive approach is it should be best able to model the reasoning and evaluative and decision-making functions of the brain. I am reminded of the computational modelling methods, used to functionally decompose a cognitive process, and are used in cognitive science (whether symbolic or subsymbolic modelling) which again aid in decision making / reasoning (see wikipedia entry)

Overall, I would say there is room for further improvement in the way we build more intelligent machines. They could be made such that they have two models of world – one deterministic , another chaotic and use the two models simulatenously (sixth stage of modelling); then they could communicate with other machines and thus learn language (some simulation methods for language abilities do involve agents communicating with each other using arbitrary tokens and later a language developing) (seventh stage) and then they could be implemented such that they have a spotlight of attention (eighth stage) whereby some coherent systems are amplified and others suppressed. Of course all this is easier said than done, we will need at least three more major approaches to modelling and implementing brain/intelligence before we can model every major unconscious process in the brain. To model consciousness and program sentience is an uphill task from there and would definitely require a leap in our understandings/ capabilities.

Do tell me if you find the above reasonable and do believe that these major approaches to artificial brain implementation are guided and constrained by the major unconscious processes in the brain and that we can learn much about brain from the study of these artificial approaches and vice versa.

Major conscious and unconcoscious processes in the brain: part 2

This is the second in the series about major conscious and unconscious processes in the brain.  The first part can be found here. This post  tries to document a few more processes / functions in the brain and their neural substrates.
To recap, the major processes  in brain (along with sample broad brain regions (grossly simplified) associated) are :

  1. Sensory (occipital)
  2. Motor (parietal)
  3. Learning (hippocampal formation in medial temporal)
  4. Affective (amygdalar and limbic system)
  5. Evaluative/decisional (frontal)
These are supplanted by the following processes and mechanisms.
6. Modeling system/ Hemispheric laterlaization: Another system/ mechanism that the brain may find useful and develop is the ability to model the world and model the self and others . This presents the following problem. The world consist of objects that follow deterministic casual laws thus lending order to it as well as seeming agents that act by their own volition and thus leading to chaos. The modeling required to model causal, deterministic world may suffer from different design constraints than that required to model a chaotic, agentic world.  The brain, I propose, solves this, by having two hemispheres, one specialized for interacting with the world based on the model of the world as orderly, deterministic , statistically regular world; while the other hemisphere specialized for interacting with the world assuming it as a chaotic , agentic, probabilistically undetermined world. The two hemispheres co-operate with each other and respond using the advantages offered by the different strategies of both hemispheres. To recap, left hemisphere is specialized for causal patterns, sequences, analysis and interpretation, classifying objects (categorical spatial represnetation) , verbal abilities depending on analysis of sequences, uses prototypes (statistical mean) and uses Match strategy of responding in a statistical pattern, Music lyrics, and works on local stimuli (components) and parses high spatial frequency and values relativity. The right brain on the other hand is specialized for random/unperdicatble associations, scenes, synthesis and documentation, acting on objects (co-ordinate spatial representation), Spatial abilities depending on synthesis of objects making the scene, uses exemplars (actual events) and uses Maximizing strategy of responding as per probability at the moment, Music melody, and works on  global stimuli (wholes) and parses low spatial frequency and values absoluteness. To summarize, left hemisphere is best suited to model temporal dimensions in an analytical and causal manner, while right hemisphere is best suited to model the spatial dimensions in an holistic and agentic manner. This modeling, it needs to be emphasized, need not be  conscious, but could be entirely unconscious and have unconscious effects. 

7. Communciation system/ perisylvian area/ mirror neurons?: Once an organism has discovered/ realized unconsciously that there are other agents/ con specifics in the world , a brain system that communicates (on an unconscious level) with the others can evolve. A system can evolve that signals the emotional/internal state to others and can also sense the emotional/ internal state of others. This can be used as an aid to predict how the agent will act – as the agent is similar to oneself, one can predict how the other will act based on its internal state by simulating how one would act himself , given the same internal state. Sensing the internal state of others is one side of the coin, the other part is signalling your own internal state honestly to others to aid communication and enhance fitness by group selection. Remember that none of these consdireations need to be conscious. Even unicellular bacteria that live in colonies/ cultures evolve communication systems based on sensing and emitting chemicals etc.  In humans the mirror neuron system activated by others actions, the emotional expression and contagious unconscious empathy may all be the unconscious communciation system driven by non-verbal communication based on mirroring and mirror neurons.

8. Attention system : The last (for now!) system to evolve might be related to directing attention or selectivity processing relevant inputs, actions, affects, evaluations, associations, models and communciations while suppressing irrelevant ones. At any time , one is bombarded by many (all unconscious ) different stimuli, urges, activated associations, body states, values, models and communications from con specifics- these may or may not be relevant to current situation/ goal.  Not everything can be processed equally as the brain has limited computational resources. This leads to a mechanism/system to gauze relevance and thus bias the other systems by selectively processing some aspects in detail while ignoring others. This attentional/orientational mechanism may be covert, may be unconscious and might be triggered by external events/ voluntarily directed; important thing to realize is that  attention seems to integrate the output and inputs of other brain systems/ mechanisms  by selectivity highlighting a few features that are relevant and coherent. This also ultimately leads to  opening the doors to the next higher level of processing by brain – the conscious processing, which is computationally more demanding and thus requires attention to restrict the inputs that it can process. The attentional system opens the floodgates of heaven (consciousness) for the humans/ animals that are able to use it appropriately.

The spotlight of attention once created leads to conscious experiences of perception, agency, memory, feelings, thoughts, self-awareness, inner speech and identity. That of course is material for another post!

Major conscious and unconcoscious processes in the brain

Today I plan to touch upon the topic of consciousness (from which many bloggers shy) and more broadly try to delineate what I believe are the important different conscious and unconscious processes in the brain. I will be heavily using my evolutionary stages model for this.

To clarify myself at the very start , I do not believe in a purely reactive nature of organisms; I believe that apart from reacting to stimuli/world; they also act , on their own, and are thus agents. To elaborate, I believe that neuronal groups and circuits may fire on their own and thus lead to behavior/ action. I do not claim that this firing is under voluntary/ volitional control- it may be random- the important point to note is that there is spontaneous motion.

  1. Sensory system: So to start with I propose that the first function/process the brain needs to develop is to sense its surroundings. This is to avoid predators/ harm in general. this sensory function of brain/sense organs may be unconscious and need not become conscious- as long as an animal can sense danger, even though it may not be aware of the danger, it can take appropriate action – a simple ‘action’ being changing its color to merge with background. 
  2. Motor system:The second function/ process that the brain needs to develop is to have a system that enables motion/movement. This is primarily to explore its environment for food /nutrients. Preys are not going to walk in to your mouth; you have to move around and locate them. Again , this movement need not be volitional/conscious – as long as the animal moves randomly and sporadically to explore new environments, it can ‘see’ new things and eat a few. Again this ‘seeing’ may be as simple as sensing the chemical gradient in a new environmental.
  3. Learning system: The third function/process that the brain needs to develop is to have a system that enables learning. It is not enough to sense the environmental here-and-now. One needs to learn the contingencies in the world and remember that both in space and time. I am inclined to believe that this is primarily pavlovaion conditioning and associative learning, though I don’t rule out operant learning. Again this learning need not be conscious- one need not explicitly refer to a memory to utilize it- unconscious learning and memory of events can suffice and can drive interactions. I also believe that need for this function is primarily driven by the fact that one interacts with similar environments/con specifics/ predators/ preys and it helps to remember which environmental conditions/operant actions lead to what outcomes. This learning could be as simple as stimuli A predict stimuli B and/or that action C predicts reward D .
  4. Affective/ Action tendencies system .The fourth function I propose that the brain needs to develop is a system to control its motor system/ behavior by making it more in sync with its internal state. This I propose is done by a group of neurons monitoring the activity of other neurons/visceral organs and thus becoming aware (in a non-conscious sense)of the global state of the organism and of the probability that a particular neuronal group will fire in future and by thus becoming aware of the global state of the organism , by their outputs they may be able to enable one group to fire while inhibiting other groups from firing. To clarify by way of example, some neuronal groups may be responsible for movement. Another neuronal group may be receiving inputs from these as well as say input from gut that says that no movement has happened for a time and that the organism has also not eaten for a time and thus is in a ‘hungry’ state. This may prompt these neurons to fire in such a way that they send excitatory outputs to the movement related neurons and thus biasing them towards firing and thus increasing the probability that a motion will take place and perhaps the organism by indulging in exploratory behavior may be able to satisfy hunger. Of course they will inhibit other neuronal groups from firing and will themselves stop firing when appropriate motion takes place/ a prey is eaten. Again nothing of this has to be conscious- the state of the organism (like hunger) can be discerned unconsciously and the action-tendencies biasing foraging behavior also activated unconsciously- as long as the organism prefers certain behaviors over others depending on its internal state , everything works perfectly. I propose that (unconscious) affective (emotional) state and systems have emerged to fulfill exactly this need of being able to differentially activate different action-tendencies suited to the needs of the organism. I also stick my neck out and claim that the activation of a particular emotion/affective system biases our sensing also. If the organism is hungry, the food tastes (is unconsciously more vivid) better and vice versa. thus affects not only are action-tendencies , but are also, to an extent, sensing-tendencies.
  5. Decisional/evaluative system: the last function (for now- remember I adhere to eight stage theories- and we have just seen five brain processes in increasing hierarchy) that the brain needs to have is a system to decide / evaluate. Learning lets us predict our world as well as the consequences of our actions. Affective systems provide us some control over our behavior and over our environment- but are automatically activated by the state we are in. Something needs to make these come together such that the competition between actions triggered due to the state we are in (affective action-tendencies) and the actions that may be beneficial given the learning associated with the current stimuli/ state of the world are resolved satisfactorily. One has to balance the action and reaction ratio and the subjective versus objective interpretation/ sensation of environment. The decisional/evaluative system , I propose, does this by associating values with different external event outcomes and different internal state outcomes and by resolving the trade off between the two. This again need not be conscious- given a stimuli predicting a predator in vicinity, and the internal state of the organism as hungry, the organism may have attached more value to ‘avoid being eaten’ than to ‘finding prey’ and thus may not move, but camouflage. On the other hand , if the organisms value system is such that it prefers a hero’s death on battlefield , rather than starvation, it may move (in search of food) – again this could exist in the simplest of unicellular organisms.

Of course all of these brain processes could (and in humans indeed do) have their conscious counterparts like Perception, Volition,episodic Memory, Feelings and Deliberation/thought. That is a different story for a new blog post!

And of course one can also conceive the above in pure reductionist form as a chain below:

sense–>recognize & learn–>evaluate options and decide–>emote and activate action tendencies->execute and move.

and then one can also say that movement leads to new sensation and the above is not a chain , but a part of cycle; all that is valid, but I would sincerely request my readers to consider the possibility of spontaneous and self-driven behavior as separate from reactive motor behavior. 

Perosnality traits: some more evolutionary perspectives

My last post  was about the David Buss chapter in The Handbook of Personality Psychology book by Hogan et al; this post is about the Arnold Buss chapter in the same book.

In this chapter, Buss considers Humans as a primate and lists down 7 personality traits that are found in most primates especially the great apes. These are:

The seven traits listed below have already been mentioned in previous sections. They may be divided into two groups.

The first involves activation, which is defined as involving various kinds of arousal (here defined broadly):

1. Activity, the total energy output as observed in rate of movements and their vigor

2. Fearfulness, wariness, running away, cowering, and the concomitant physiological arousal

3. Impulsivity, acting suddenly and on the spur of the moment; the opposite is the tendency to inhibit behavior

The second set of personality traits are all social:

4. Sociability, preferring being with others (though primates are a highly social group, there are still individual differences in sociability within each species)

5. Nurturance, helping others, especially those who need help, even at a cost to the helper (altruism)

6. Aggressiveness, attacking or threatening others

7. Dominance, seeking and maintaining superior status over others versus the opposite pole, submissiveness

I would like to group them slightly differently ( and in accordance with my eight stage theories) and also introduce another trait that of suspiciousness when we consider humans as other primates have a rudimentary ToM ability.

  1. Fearfulness mapped to Neurtoticsm.
  2. Impulsivity mapped to Conscnetiousness
  3. Sociability mapped to Extraversion
  4. Nurturance mapped to Agreeableness
  5. Dominance mapped to Rebelliousness/ Conformity
  6. Suspiciousness mapped to Trust/Defensiveness
  7. Activity mapped to Activity
  8. Agressivenss mapped to Masculinity/Feminity
He also lays down the framework for how such traits may become evident ; he works within attachment theory paradigm and highlights research on primate attachment studies to lay down the foundation for why such traits may develop in an individual.

The period of attachment in primates has been divided into three phases (H. F. Harlow, Harlow, & Hansen, 1963). At first the mother is solicitous and completely accepting of the infant, and she is a haven of safety and nurturance.

The infant’s feeling of security depends in large part on the mother. If she is sufficiently protective and available, the infant will be secure enough to venture out in the wider environment. Primate infants appear to be motivated by two opposing tendencies: the need to seek novelty and stimulation versus the need for security and protection (Mason, 1970). An insecure infant remains close to the mother, too scared to explore the environment. A secure infant tends to be low in fear and can venture away from the mother so long as she is in sight.

In the second phase of attachment, the mother withdraws affection, diminishing attention to the infant, and starts to punish the infant. The latter may react with withdrawal, anger, resistance, or negativism. These first signs of independence are typically met by even more irritabihty and punishment by the mother.

In the third phase, the mother is often occupied with the birth of the next offspring and therefore is even more rejecting of her older child. The presence of this new infant is likely to elicit jealously and temper tantrums by the displaced sibling. If the mother can spare some attention and affection for her older sibling, the latter’s jealousy and annoyance should gradually wane.

The events of the attachment period may be expected to affect personality traits. The mother’s behavior should be regarded as only one determinant, albeit an important one, of her youngster’s personality. If she is not sufficiently protective and a haven of security, her infant may become fearful and inhibited. If she fails to provide enough attention and social stimulation, her infant may become withdrawn and less sociable. And if she cannot share at least some affect with her older offspring after the birth of a new one, the older one may become intensely jealous. In brief, the events of attachment are assumed to affect the personality traits of fearfulness, impulsivity (the opposite of inhibition), sociability, and the anger component of aggressiveness (jealousy).

To me this seems to be valid developmental trajectory of the traits: A non-protecting mother leading to Fearfulness (N); not providing a safe haven leading to lack Impulsivity or Inhibition (C); not providing enough attention leading to less sociability (E); not providing social stimulation and care leading to lack of Nurturnace in child (A) (which Buss doesn’t touch upon) and finally not sharing affect leading to Jealousy/ Dominance problems within siblings(Rebelliousness/Conformity).

Before we accept this attachment theory in its entirety it is apt to pause and remeber that many times the behaviour of mother is driven by infant behaviour and that mother and chil may share the sam temperamental quality due to genes and not due to nurturing and this however reflects in a pattern of traits in child and parenting practice in parent.

Finally Buss goes on to show how some of the traits in other primates are not well developed as compared to humans and are at the level of human infants and thus cannot lead to much insight about human personality. One exapmle is that of self-awareness; though primates and human infants may have a mirror-test self-awareness, it is limited.

Adult humans are capable of mirror-image recognition, which is absent in infants and develops slowly during the second year of life as part of more general trends in cognitive development. By the age of 2 years most infants possess this capacity (Amsterdam, 1972; Schulman & Kaplowitz, 1977). Does this mean that children of 2 years have a self-concept and the same kind of self-awareness as older children and adults? There are five cognitive attributes present in older children that are absent in 2-year-olds, which suggests that the answer is no.

The first is self-esteem. The basis for later self-esteem may be laid down in 2- year-olds, but children of this age do not show behavior that allows us to infer the general self-evaluation called self-esteem. This diffuse feeling of self-worth develops gradually and can be measured perhaps by the age of 4 years. Nor are infants clearly aware of the difference between their private feelings and public behavior.

It is still too early for the sense of covertness and an awareness that private thoughts and feelings cannot be observed. Infants and primates lack the sense of covertness that can be inferred in children of 4 years. Infants are still egocentric and do not know that others view the world from different perspectives. Even children of several years of age are Umited in social perspective-taking. In one study children were asked to select gifts for their parents, teacher, brother, sister, and self (Flavell, 1968). Most 3-year-olds selected the same gifts for others as for themselves. Some 4-year-olds selected gifts appropriate for others, half the 5-year-olds did, and all the 6-year-olds did. Social perspective-taking evidently emerges during the fifth year of life. Linked to perspective-taking is the abihty to view oneself as a social object. Such public self-awareness, as seen in the reaction of embarrassment, does not occur until the fifth year of life (Buss, Iscoe, & Buss, 1979).

The last facet of the advanced self to develop is identity. It may be a personal identity, the sense of being different from everyone else in appearance, behavior, character, or personal history, or it may be social identity, knowing oneself to be a member of a nation, religion, race, vocation, or any other group that offers a sense of belonging to something larger than oneself. And most of us have a sense of continuity, identifying ourselves as the same person across decades of time or across diverse social roles.

Thus five aspects of the self are absent in 2-year-old human children: selfesteem, a sense of covertness, perspective-taking, public self-awareness, and identity. These may be regarded as evidence for an advanced or cognitive self, which is conspicuously absent in human infants and the great apes. They do appear to have a primitive, sensory self—an awareness of where the body ends and not-me begins, and mirror-image recognition (Buss, 1980). But they lack the advanced cognitive self that is implicit in constructs such as self-concept, self-esteem, selfconsciousness, and identity, constructs easily applied to older human children and adults.

To me this beautifullay sums-up what we can and cannot derive from studies of primates and other mammals about human personality.

References: Buss, H. Arnold. (1997). Evolutionary perspectives on personality traits. In R. Hogan, J. A. Johnson, & S. R. Briggs (Eds.), Handbook of Personality Psychology (pp. 345-366). New York: Academic Press..

Personality traits: evolutionary perspectives

I have been reading and enjoying The Handbook of  Personality Psychology by Hogan et al, and found the chapter written by David Buss particularly useful.

Here I would like to expand on the idea and while buss explicitly does not want to indulge in a discussion of a few psychological tendencies and associated behavioral class acts; I would like to walk exactly that particular path.

First to recap,

Humans, like other organisms, can be viewed as organized structures that exist in their present form because of a long history of natural selection, operating over millions of years. Each one of us owes our existence to a long and unbroken line of ancestors who successfully solved problems posed by survival and reproduction in our evolutionary past. Therefore, human structures, as well as human psychological mechanisms, at some fundamental level of description, can be analyzed in terms of the problems they solve.

But “survival” and “reproduction” are broad categories, each subsuming a large and complex array of subproblems. To the extent that the evolutionary psychologist can identify the nature of the specific problems that humans have evolved to solve, she or he has some advantage over the nonevolutionary psychologist in discovering the nature of human nature.

Buss then goes on and breaks the survival and reproduction into many component and also adds genetic investment to the mix. I parse the same data in my own way and generate the hypothesis that the most important concern of any living organism, and especially humans are survival, genetic investment and reproduction.

Survival behavioral tendency can be further split in three parts: one pure survival as in escape from predators or death; I’ll refer to this as Foes! the second concerns growth or acquiring resources necessary for thriving and I;ll call this Food. The third maintaining one’d edge in avoiding foes and finding Food by building alliances with con specifics. I’ll call this Friends. Thus survival is characterized by the three F’s of Foes, Food and Friends!

Genetic investment can be split into two K’s that of Kids and Kins. The first tendency that of Kids is concerned with issues of parental investment and care of offsprings.the second that of Kin is concerned with how to help other genetic related individuals at minimal cost to self such that maximum fitness ensues.

Reproduction can be split into three parts that of mate selection, that of mate attraction and that of mate retention. I’ll call these the three S’s of reproduction(Sex is *NOT* one of them!). The first task is to Select the right mate; the second task is , that once you have zeroed in on a suitable mating partner, you have to court and attract the partner, I call this function Seduce; the final task, especially in long-term pair bonded species like Humans is to guard or retain the mate, I call this Securing the mate.

What I propose is that given these Eight tasks ( 3 survival, 2 investment and 3 reproductive tasks ) that each species has to solve, each specie would evolve some mechanism to solve these problems that are species-typical; however there would be individual variation to the extent that the extent to which an individual organism is driven by that particular conscious motivation/ behavioral tendency and gets into environments and situations that trigger that particular task would determine the psychological mechanism that drives that individual.

To make things more clear , what I am proposing is that there are bound to be individual differences in the relative importance of these psychological mechanisms for an individual- thus a human may be primarily driven by mate selection concerns at a particular age- while another may be forever primarily concerned with safety, security etc- and this would be the first factor that would lead to individual variation in personality. Moreover, I am proposing something radical, that depending on the environment, there may be two extreme types of responding to each of these tasks- and the second most important variation that we get from person to person – is in whether one habitually and instinctively (genetically determined) responds in one way or the other as one faces the task and whether or not one factors the environment and context in which the task demand is made or whether ones behavioural tendency is fixed and inflexible.

To take by way of an example, lets us focus on the Kids part of genetic investment. It has been well documented that their are two types of parental strategies r-type and K-type; now a species may have predominantly K-type investment strategy, but within the species individual organisms would differ in their reproductive strategy around the mean in K-type and r-type directions. thus, Humans exhibit predominantly K-strategy, but Africans show more r-type and Asians more K-type. It is equally well documented that these r-type and K-type strategies are actually responses to the external environment (food abundant, predictable , stable environment etc) and thus, though a species has a set point, there is enough individual variation such that in changing environemnetal conditions at least one sub type is able to thrive and survive and reproduce and invest!

To take another example from Buss, Absence of father leads to short term mating strategy in daughters (amongst other things like premature puberty etc) and this environmental facyor may be the most important environment variable as related to Securing task of retaining the mate; if one sees the father as absent from home, one may think its wise to go for a short term mating strategy as the culture is one that encourages low stability of pair bonds; this might be a justifiably welcome strategy; on the other hand it might be genetically the case that someones set point is set towards short-term relationships.

I will now claim that the eight personality traits I had outlined earlier are directly related to these eight evolutionary task (see here for another slightly different list of the eight tasks ) that one faces- and more so are mapped one-on-one with the same ordered mapping!


  1. Foes (survival 1) : A behavioral tendency to be on the lookout for foes / troubles leading to Neuroticism trait. The extremes of courage/calmness and fear/anxiety  are driven by what type of environment one lives in – whether it is full of dangerous objects or not so! One prediction is that those high in N should have more Phobias and vice versa. 
  2. Food (survival 2):A behavioral tendency to acquire resources leading to Conscentiousness. The extremes of ambition/ covetousness and laziness/ easy-going are driven by whether the environment is abundant in resources or lacking thereof! One prediction is that those high in C should be more readily diagnosed with OCD and vice versa.
  3. Friends (survival 3):A behavioral tendency to form alliances leading to Extraversion. The extremes of sociability and seclusion dependent on some environmental factor (like how important is community interference in day to day activity) . Might be related to mean group size (150 in humans)
  4. Kids (investment 1)   A behavioral tendency to invest in ones offsprings leading to Agreeablness. the extremes of care/ empathy vis-a-vis apathy/ psychopathy may be driven by the same concerns that decides whether to go for r-strategy or K-strategy.
  5. Kins (investment 2) : A behavioral tendency to help one kins leading to Conformity / Rebelliousness: Here it is instructive to note that older siblings are generally conformists while younger siblings are rebellious – thus age-order and environmental variable may decide whether one would be conformist or rebellious and this somehow affects your behavior towards sibling and his/her reproductive fitness. Also, irrespective of your birth order in the family (kin) , due to variation, some may be genetically predisposed to be conformists and other rebellious!
  6. Selecting (reproduction 1) : A behavioral tendency to judge others intentions etc accurately and thus determine who is a suitable candidate for mating/trusting  leading to Trust/Defensiveness. The extremes of trust and suspicion may be adaptive in environments differing with respect to levels of promiscuity; in a highly promiscuous and cheating/ cuckolding environment it may pay to be suspicious.     
  7.   Seducing (reproduction 2): This behavioral tendency of intra sexual competition can be broken into three components: i) Testing against own sex con specifics(building better muscles for men) ii) Embodying preferences of opposite sex (Chauvinism in case of Males) and the third I havent been able to figure yet!! The extremes of too much effort/activity  in seducing as against the extreme of being dull/boring and uninterested in other sex leads to the dimension of Activity
  8. Securing (reproduction 3) : A behavioral tendency towards sociosexuality;At one end of this dimension are individuals who are “restricted” in sociosexuality—they require more time, attachment, and commitment prior to entering a sexual relationship. At the other end are those who are “unrestricted” in sociosexuality—they require less time, attachment, and commitment prior to sexual intercourse. These extremes may lead to the trait of Masculinity- Feminity in how one guards and forms a pair bond.

I would thus end my argument; to me the eight stage process is compelling- I am sure with each passing day there are more converts to that developmental and evolutionary eight stage theory.

References: Buss, D. M. (1997). Evolutionary foundations of personality. In R. Hogan, J. A. Johnson, & S. R. Briggs (Eds.), Handbook of Personality Psychology (pp. 317-344). New York: Academic Press..

Novelty Seeking and Reward Dependence: the dopamine white matter connection.

I had earlier wrote extensively on Cloninger’s personality temperaments and proposed that dopamine lies behind the trait Novelty Seeking; while norepiniphrine lies behind Reward Dependence trait. New research , as reported in Nature Neuroscience makes me rethink some of that simplistic schema.

As per Cohen et al, they have found a double dissociation between white matter connectivity between dopamine and sub-cortical and cortical regions and found that these white matter connectivities differentially predict and correlate with traits novelty seeking and reward dependence. Let me quote from the article:

Myriad cognitive, emotional and motor functions of the brain rely on the integrity of the striatum and on interactions between the striatum and other cortical and subcortical networks1, 2, 3. Lesion work in animals supports the idea that fronto-striatal connectivity is crucial for aspects of behavioral adaptation and learning. In these cases, it is clear that anatomy constrains function. Here, we investigated whether anatomical connectivity underlies more global aspects of behavioral and cognitive organization: human personality. We found that the strength of connectivity between two different striatum-related networks predicted individual differences in self-reported personality traits in humans.

Then they go on to show which two networks they studied and found the dissociation in.

In humans, novelty seeking is characterized by impulsivity, exploratory drive and excitability, and has been proposed to be driven by individual differences in dopamine system sensitivity. In rats, both striatal dopamine and hippocampus inputs modulate novelty seeking, linking these structures into a network for novelty detection. The hippocampus may support novelty seeking in part by signaling when sensory input differs from memory-driven expectations (that is, a sensory prediction error), whereas the amygdala may support novelty seeking by modulating hippocampal and striatal activity in novel environments or during emotional memory encoding. Our findings provide additional support for this novelty-loop theory by demonstrating that the hippocampus– and amygdala–ventral striatal pathways are related to stable individual differences in novelty seeking personality.

High reward dependence is characterized by several cognitive, emotional and social facets, including enhanced learning from reward signals, persistence in repeating actions associated with rewards, high sociability and reliance on social approval. These functions recruit the striatum, including dorsal regions. Indeed, the tracts predicting reward dependence were not confined to one particular subregion of the striatum, but were instead observed in striatal areas in which there were strong inputs from these seed regions . This suggests that the white-matter circuits subserving reward dependence are distributed throughout multiple cortico-striatal loops. These loops have been linked to processes ranging from reward learning to cognitive control to action selection.

From the above it is clear that the striatal dopamine system is implicated in both Novelty seeking and Reward dependence. While the implicit, first-line, sub-cortical ’emotional’ and unconscious processes sub served by hippocampus and amygdala may be the white tract inputs to the striatum that result in Novelty seeking behavior; the explicit, second-order, cortical, ‘cognitive’ and conscious processes sub served by frontal cortex may be the white matter inputs to the striatum that result in reward dependence behavior.

This indicates that the stage theories are true!! If one considers the sub-cortical responses to be immature and the cortical responses to be more mature than moving from novelty seeking focus to reward dependence focus is a move up the stages. What I propose is that each stage marks a movement from sub-cortical input reliance to cortical input reliance and also involves novel mechanisms and systems.

Thus, as per my theory, in the first stage of personality development, or for the trait Harm Avoidance, the white matter connections implicated should be between sub-cortical regions and raphe nucleus ( the serotonin system).

In stage 2, or for trait Novelty seeking, the white matter tracts involved should be between cortical regions and Raphe nucleus (serotonin system). Also as the earlier serotonin system comes moer and more unedr cortical control, the second system based on dopamine becomes active but is under sub-cortical control. Thus, white matter tracts involving sub-cortical regions and striatum/ VTA should also be involved.

In stage 3, or for trait Reward Dependence, the white matter tracts should be between cortical regions and striatum/ VTA as the earlier dopamine system predominance us reigned in and a new system based on nor-epinepherine replaces it. This nor-epinepherine will be under sub-cortical control and white matter tracts from sub-coritcal regions to locus ceruleus should also be involved.

And this same scheme should go on for fourth (epinepherine), fifth (histamine/ melatonin), sixth, seventh and eighth stages/ personality traits.

All these are testable hypothesis and can be easily verifed. If verified, they can shed immense light on how perosnality develops and what do temperaments/ character strengths really mean.

Hat tip: Neurological correlates
Michael X Cohen, Jan-Christoph Schoene-Bake, Christian E Elger, Bernd Weber (2008). Connectivity-based segregation of the human striatum predicts personality characteristics Nature Neuroscience DOI: 10.1038/nn.2228

Primate Evoloution: stage I: prosimians and predation

In my last post  I hinted at how primate evolution may be an example of eight stage evolutionary process in action and today I’ll try to support my first prediction that the prosimian stage evolution was dominated by predatory concerns.

Prosimian evolution and branching within the primate order took place 55 million years ago or a bit earlier, near the beginning of the Eocene Epoch. These first primates , it is safe to assume were nocturnal just like today’s prosimians like lemurs, bushbabies, tarsiers etc are. Why they were nocturnal remains a question to be answered. Species turn nocturnal usually to avoid predation by day predators. Crypsis  is the mechanism that even today is used by prosimians to avoid predation.

It is instructive to note here that though predation in primates has not been considered a big force, in pro-simians it is important. A whole book Primate anti-predator strategies  has been written which focuses more on pro-simian anti-predator strategies than on other primates. It is testament to the fact that predation was/ remains important for prosimian evolution. Here I quote from the preface of the book:

The impact of predation on the morphology, behavior, and ecology of animals has long been recognized by the primatologist community (Altmann, 1956; Burtt, 1981; Curio, 1976; Hamilton, 1971; Kruuk, 1972). Recent thorough reviews of adaptations of birds and mammals to predation have emphasized the complex role that predation threat has played in modifying proximate behaviors such as habitat choice to avoid predator detection, degree and type of vigilance, and group size and defense, as well as ultimate factors including the evolution of warning systems, coloration, and locomotor patterns (Thompson et al., 1980; Sih, 1987; Lima & Dill, 1990; Curio, 1993; Caro, 2005).

We have conducted research on nocturnal primates for more than ten years. Immersed as we have been in the literature of nocturnal primatology we recognize a spectrum of diversity amongst the nocturnal primates in their social organization, cognitive behavior, and ecology (Charles-Dominique, 1978; Bearder, 1999; M¨uller and Thalmann, 2000). Our studies on tarsiers and lorises showed that these species were highly social and that resource distribution was not sufficient to explain why they defied the supposed “stricture” of being solitary (Gursky, 2005a; Nekaris, 2006). Furthermore, our animals defied another supposed “rule” — namely, that all nocturnal primates should avoid predators by crypsis (Charles-Dominique, 1977). Even recent reviews of primate social organization and predation theory included one-sentence write-offs, excluding nocturnal primates from discussions of primate social evolution on the basis that crypsis is their only mechanism of predator avoidance (Kappeler, 1997; Stanford, 2002).

An analysis of the mammalian literature shows this type of generalization to be crude at best. Small mammals are known to have extraordinarily high rates of predation, and a plethora of studies of rodents, insectivores, and lagomorphs, among others, have shown that predation is a viable and powerful ecological force (Lima & Dill, 1990; Caro, 2005). Furthermore, although researchers have long considered it critical to include prosimian studies in a general theoretical framework concerning the evolution of the order Primates (Charles-Dominique & Martin, 1970; Cartmill, 1972; Oxnard et al., 1990), a pervading view contends that prosimians are too far removed from humans for the former’s behavior to shed any light on the patterns of behavior seen in anthropoids (Kappeler & van Schaik, 2002; Stanford, 2002).

However, an excellent review by Goodman et al. demonstrates the dramatic effect predation can have on lemurs, and it remains the most highly quoted resource on lemur predation, despite that it was published in 1993. Studies of referential signaling aid in dispelling the view that prosimians are primitive and not worthy of comparison with monkeys and apes (Oda, 1998; Fichtel & Kappeler, 2002). A handful of studies further reveal that prosimians are not always cryptic and may engage in social displays toward predators (Sauther, 1989; Sch¨ulke, 2001; Bearder et al., 2002; Gursky, 2005b).

Leaving for the time-being the fact that prosimains too engage in social behavior as a defense against predation, and sticking to the traditional view that crypsis best defines their defense mechanism, the thing to be noted is the relative abundance of predatory strategies on prosimian evolution. A whole book has been written keeping that in mind!!

So my thesis is that for the very first stage of evolution when a leap was made, prosimains got left behind, still struggling with predation; while the common ancestor of new world and old world primates somehow solved/ reduced the problem of predation and became diurnal and maybe started living in large social groups and thus exhibiting social defenses against predators. This evolutionary successful completion of the first developmental/ evolutionary task of avoiding predators, then enabled these ancient primates to focus their energies on finding food and thus from insectivores become fruit-eating and move towards a rich diet and focus on acquisition of resources. but that takes us to stage II marked by focus on food and the new world monkeys. More on that later!

Primate evolutionary tree: a case of eight stage evolution leading to humans?

I have been looking at primate evolution and taxonomic tress for quite some time and am aware that different scholars parse the same tree in different ways, specifically people try to avoid being anthropocentric. I , on the other hand , will focus exclusively on the primate tree as it relates to humans and try to to show that it might be a living proof of the eight stage theory of evolution/ development.

First let me show you a popular way of portraying the primate tree from Philadelphia Inquirer’s Going Ape website.

Now, let me show you an alternative classification (just slightly different from this, but based on cladistics) . It is hard to see the figure (I’ve lost the original full -kleght versions), but the idea is that the first level branching happens at the level of suborder, then infraorder, then family etc within the order of primates.

Here is a similar diagram from the The Third Chimpanzee by Jared Diamond.

It is instructive to note that here barnching within primate tree is as follows:

  1. Suborder branching: Prosimians: I hypothesize that prosimian evolution be driven by first adaptive problem that of hiding from / avoiding predators. (lemurs etc)
  2. Infraorder branching: Platyrrhine (flatnosed) or New World Monkeys: I hypothesize that these would be most adventurous of all and would be focussed on finding food and resources, having mastered the predation problem. Maybe the main factor here would be their range size etc. This family is as opposed to Catarrhine (down-nosed) or Old World primate to which humans belong.
  3. Superfamily branching: Cercopithecoidea: Old World Monkeys. Lets say we focus on old world monkeys here. The hypothesis is that they would be specialized for forming alliances and territorial hierarchical behaviors. This superfmaily is as opposed to hominoidea superfamily.
  4. Family branching: Hylobatidae or Gibbons: the hypothesis is that Gibbon evolution may be driven by parental investment conflicts. this family is as opposed to Hominidae to which humans belong.
  5.  Subfamily branching: Ponginae or Orangutans :  Orangutan evolution may be driven by kin selection concerns.
  6. Tribe branching: Panini or gorillas: Gorilla evolution may be driven by theory of mind considerations. Maybe the driving force behind gorilla evolution is reading others mind and we would find good evidence for the same in gorillas. 
  7. Species branching: pan of chimpanzees and bonobos and humans: may be driven by communication or language concerns. Of course language or communication in Humans is phenomenal; but may be of equal importance for the other two also.
  8.   This species may be a branching of humans later on along sexual selection lines or assortative mating considerations along the lines of Elois and Morlocks.
I am not a primatologists and the above appears too simplistic and fishy to me; but is there evidence for any of the  hypothesis presented above; if so do let me know! Meanwhile I will be on the lookout for any confirmatory evidence!!

The eight major evolutionary transitions

Regular readers of this blog can vouch for my fascination with the eight stage  theories and would no doubt be sympathetic when I report my exhilaration of finding that none other than Maynard Smith himself has proposed that there are eight major evolutionary transitions till date in the evolution of life. Maynard Smith and  Szathmary in their book The Major Transitions in Evolution had proposed for the following eight transitions :

More details are available at this wikipedia page . now I , independent of any knowledge that this has already been proposed by Maynard Smith as back as in 1995, a few days ago had come up with similar eight transitions in evolution of life forms . Of course there are some differences, but the important thing to note is the similarities(great minds think alike) and of course my model is far more accurate and realistic than Maynard smiths who I believe leap from multi-cellular organisms to humans quite arbitrarily leaving all the phylum in between un addressed.

I’ll now briefly note the similarities and also highlight the dissimilarities in our approaches:

The first three stages are identical (first description of Maynard Smith stage and that is followed by my description in a few days ago post) :

1. Transition from Replicating molecules to “Populations” of molecules in compartments
1. Co-Evolution of genes and proteins/ amino-acids

2. Transition from Independent replicators (probably RNA) to Chromosomes
2. Evolution of the chromosome or two strands of DNA

3. Transitions from RNA as both genes and enzymes to DNA as genes; proteins as enzymes (Prokaryotes)
3. Evolution of a simple unicellular prokaryotic-bacteria-like cells

In the fourth stage I differ a bit from Maynard Smith, in that I propose for an intermediate archea type life-feom evolution while they jump straight to prokaroyotes)
4. Trasition from Prokaryotes to Eaukaryotes
4. Evolution of simple unicellular Archea-like cells

In the fifth stage they stress the importance of sex. I stress the importance of organalles, mitochondria and nucleus (specialized cell structures) instead.
5.Transition from Asexual clones to Sexual populations
5.Evolution of simple uni-cellular Eukaryotic like cells

In the sixth stage they move directly to multi-cellular organisms while I introduce intermediate colonies. I believe their fifth stage sexual populations are a substitute for my colonies (both map to protists)
6. Transition from Protists to Multicellular organisms — animals, plants, fungi
6.Evolution of simple colonies of cells (first animal phylum: the porifera or sponges)

In the seventh stage they make a leap and go directly to full-fledged solitary individuals (animals, plants fungi) while I take a more conservative approach and introduce multi-cellular organisms now from colonies.
7. Transition from Solitary individuals to Colonies with non-reproductive castes
7. Evolution of multi-cellular organisms with digestive tracts (second animal phyla coelenterate)

In the eighth and final stage they leap from primates to humans while I stay with multi-cellular organisms but introduce a CNS for the first time.
8.Transition from Primate societies to Human societies with language, enabling memes
8. Evolution of multi-cellular organisms moving towards a CNS( bilaterality) (third animal phyla :Ctenophora (Comb Jellies)):

I believe that after multi-cellular organisms they have made big leaps (which may be justified in some contexts), but I have worked more on micro level and believe that we can gain much more by studying the intermediate phyla too. The important thing to note is the common evolutionary and taxonomic approach and the guiding principles as outlined below for each transition:

Maynard Smith and Szathmary identified several properties common to the transitions:

  1. Smaller entities have often come about together to form larger entities. e.g. Chromosomes, eukaryotes, sex multicellular colonies.
  2. Smaller entities often become differentiated as part of a larger entity. e.g. DNA & protein, organelles, anisogamy, tissues, castes
  3. The smaller entities are often unable to replicate in the absence of the larger entity. e.g. Organelles, tissues, castes
  4. The smaller entities can sometimes disrupt the development of the larger entity e.g. Meiotic drive (selfish non-Mendelian genes), parthenogenesis, cancers, coup d’état
  5. New ways of transmitting information have arisen.e.g. DNA-protein, cell heredity, epigenesis, universal grammar.

Hat Tip: Shared Symbolic Storage blog

Goals of Psychology and major persoanlity theory groupings

I recently came across the All Psych  website which I found to be a very good resource for anyone interested in Psychology.  I was reading the Personality synopsis section and was struck by the goals of psychology delineated there :

Psychology is the study of thoughts, emotions, and behavior, and their interaction with each other and the world. There are five basic goals of psychology:

1. Describe – The first goal is to observe behavior and describe, often in minute detail, what was observed as objectively as possible

2. Explain – While descriptions come from observable data, psychologists must go beyond what is obvious and explain their observations. In other words, why did the subject do what he or she did?

3. Predict – Once we know what happens, and why it happens, we can begin to speculate what will happen in the future. There’s an old saying, which very often holds true: “the best predictor of future behavior is past behavior.”

4. Control – Once we know what happens, why it happens and what is likely to happen in the future, we can excerpt control over it. In other words, if we know you choose abusive partners because your father was abusive, we can assume you will choose another abusive partner, and can therefore intervene to change this negative behavior.

5. Improve – Not only do psychologists attempt to control behavior, they want to do so in a positive manner, they want to improve a person’s life, not make it worse. This is not always the case, but it should always be the intention.

To me the five major goals of psychology follow the five general stages that I usually talk about:  The first stage in my analysis of disparate phenomenons begins with it being descriptive and focused on clearly delineating the phenomenon under study and is generally biological. The second stage usually tries to find the impulses or reasons behind the phenomenon and is more related to explaining causes for the phenomenon and is generally related to motivation. The third stage  is usually concerned with development of phenomenon such that we can get some basic predictive properties in the mundane real world and is generally related to outward behavior. The fourth stage is usually focussed on how the phenomenon can be kept in check and is generally related to social dimensions (conformity and peer pressures). The fifth stage is usually related to how the phenomenon sort of gets a unique personal flavor and is generally related to individualistic and individuation dimensions.

Now, as an example I will try to make a case that though all the major theoretical approaches in personality psychology make use of all the stages and have as their goal all the five goals as delineated above; some of them are more focussed on one particular goal/ stage and thus are characterized by that goal/ stage.

Let me briefly review the major theoretical approaches to personality psychology below in the light of this framework:

  1. Trait / Biological approaches to personality: I believe it is fair to group the biological and trait theories under the same group as the major feature of these theories is to outline the number of factors that can be used to describe a personality adequately. They are primarily descriptive in nature. One can argue that biological theories also explain the traits in terms of underlying biological markers; but that is juts begging the question one level down. Why does neurotransmitter system A over activation lead to this observable trait? They just describe the higher trait in terms of a lower biological phenomenon and are very good at descriptive level; but they lack explanatory powers.
  2. Psycho dynamic/ Psychoanalytical theories:  These theories, the most famous being that of Freud, try to explain the personality and are totally obsessed in trying to find reasons for all and sundry observable phenomenon including accidental slips of tongues.  these are very good at explanatory levels, but not very good at other levels like predicting personality from childhood experiences or even in adequately describing the personality structure. They are more focussed on dynamics and less on structure. 
  3. Behavioristic/ behavior genetics theories: These theories , the most famous being Skinnerian theories are most concerned with predicting behavior based on past experiences/ learning. These are the S-R or CS-CR theories and operant theories; the primary motivation not being to either describe or to explain personality; but just to predict how a behavior can be predicted given a personality (previous behavioristic learning).  Thus the primary focus on the ability to predict phenomenon and applications too limited to situations and traits that can lead to predictability.  
  4. Social learning/ Cognitive theories: These theories like that  of Bandura, Beck etc are more concerned with how personality can be ingrained or learned and controlled. Both Bandura’s bobo doll experiments as well as CBT point to the direction and focus of these approaches: what are the right conditions of personality formation and how that process can be controlled either by providing right role models/ environments conducive to social learning or by changing our cognitive schema. The action has moved away from describing or explaining or predicting to controlling how a good and socially acceptable personality can be formed/ learned.
  5. Existential – Phenomenological theories:  These theories, like that of Maslow, are more concerned with how to improve one’s personality. The focus is on flows, self-actualization, self-transcendence or whatever. One has moved away from mere description, analysis, prediction or control to actually thinking about what is a good personality and how to attain it; hence the primary focus on finding meaning; finding full potential and on improvement and positive psychology
I am sure there are other approaches to personality that I have not covered here- like the evolutionary theories; but than what else are the next three stages for, if not to make room for more such approaches!!
Do let me know if you disagree that the major approaches to personality theory follow a patterns and sort of stages and are primarily concerned with one primary goal at the cost of the other.