Saturday, May 30, 2009

What it is like to be a zombie?

I am sure many of you are already familiar with Nagel's perennial question 'what it is like to be a bat?'  (see this one with some added commentary too). Today I propose to ask a slightly different question 'what it is like to be a zombie'? That may seem absurd at the outset, as in many people's mind Zombies are synonymous with no consciousness. I beg to differ. As I have already indicated in my last post on major conscious and unconscious processes in the brain, there is an easy problem of A-consciousness and there is a hard problem of P-consciousness. I have already tried to breakup A-consciousness in its parts and  I similarly think that P-consciousness is much more that qualia (qualia I envisage as more grounded in sensory or perceptive systems). So given the fact that most zombies are behaviorurally indistinguishable from normal humans, and given the fact that most people who argue for zombie models of humans (that 'there is no one home to watch/direct the picture') do still endow the zombie and themselves with the A-consciousness aspects - they do not deny that a representation is made and is consciously available for processing (the theater of consciousness) , it is reasonable to speculate that although lacking full P-consciousness, it would still be something like to feel like a zombie. Let me draw an analogy, in some dissociative disorders, one starts seeing the world as unreal (derealization)  and the self as unreal (depersonalization) ; yet even though one believes oneself to be unreal there is still something it is like to exist in that 'unreal' state.

Similarly, though one may model oneself and others as zombies, still it would be something like it is to be in a state that thinks and believes that one is a zombie and also acts accordingly. I am making a leap here. I am assuming that awareness or modeling of ones A-conscious experiences leads to or affects one's phenomenal consciousness. Thus, in my view , someone who models oneself and others as a zombie, would have a different sort of P-consciousness or what it feels-to-be-like, than a person who models oneself and others as sentient agents  and his P-cosnsciousness would be of a different nature.

Now consider the problem we face when confronted with a world which is deterministic and chaotic at the same time, and which is inhabited by agents which seem to be unpredicatable and constrained at the same time. I have already indicated elsewhere, that people may form tow types of model- one is a statistical/ deterministic model that they may apply to the world; another is a probabilisitic/agentic model that they may apply to the self (as well as other sentient beings).  If one keeps these domains of folk-physics and folk-psychology separate, all is hunky dory; all hell breaks lose (pun intended; zombies are correlated with dead apocalypse scenarios in popular culture) when one applies a deterministic  model (that fits the world) to the self/others. Similarly all hell breaks loose, when one applies an agentic/indetrminsitc model (that fits the sefl/others) to the world.

For today, we will focus on the problem of modeling self, and leave the problem of modeling world for a later day. A self may act differently in many similar/same situations. If it acts the same on each occasion, given the same situation; we can easily say that the situation causes the action. This poses no problem for the zombie (I will refer to a zombie as a person whose self/other conceptualization is as that of oneself/others as machines), as one has a deterministic rule that defines the self- (given situation A-> action B), and thus one can keep one's model of self as-a-deterministic-being consistent. On the other hand, if the situation A sometimes leads to action B, but at other times to action C, then one has to explain the variance in the behavioral output. Consider first the problem of explaining the variance between-subjects. Given the same situation A, subject Z acts in way B while the subject Y acts in way C.   There is considerable variance. If one assumes all selves as created equal, then all should have behaved similarly. Either one has to grant an extraordinariness and uniqueness to all selves, or if one has a statistical  and ordinary nature of human beings, one has to grant that the subject given the same situation, should have behaved identically. But we all see that there is considerable variance.  This variance is individualistc and one may try to explain this between-subjects variance using subject's personal history (prior conditioning: a behavioristic model; or repressed emotional experiences/memories: psychoanalytical theory), one may also look at subject's common ancestral history and use that to explain behavior (genetic differences: evolutionary biology; cultural differences : anthropology ) or one may even look at his holistic experiences and use that individualistic experiential history as a basis for explaining behavior ( consider two identical twins that because of their different sampling of environment may end up as differently conditioned etc). Phew that covers all the major psychological theories that I could remember.

Now lets focus on the problem of explaining within-subjects variance ; given the fact that the Situation is the same (situation A)  and the subject is the same (subject Z), why does the same subject react differently to the same situation (acts in ways B and C). This is a relatively hard problem. One could deny the problem itself and claim that no situation is identical, but hey we are doing armchair philosophy right now, and we have already agreed to the premise of existence of a same situation A when we discussed between-subjects variance above, so it doesn't hurt to concede that the situation A can be same for subject Z, but he may still react differently in ways B and C. None of the above psychological approaches, if applied in a strict, causal deterministic sense can explain the same subject Z reacting differently to situation A , as the subject Z's personal history (conditioning, repressed memories) or ancestral history (genes, cultural influences) or even previous experiences and choices remain the same and thus should ideally have led to the same behavior. I am making an assumption here that situation A is repeated twice or more in succession (closely in time) so that one cannot counter and say that conditioning (to take an example) has changed in meanwhile due to situation A itself and thus, as the subject Z (at time t=1) has changed to an extent (by delta effect of situation A on the 'earlier' subject Z at time t=0) , so he may react differently at tome t=1 from how he reacted at time t=0.   What we are really doing is doing away with a term of the equation; we are saying subject Z is not constant (it  keep changing- self as constantly changing- a Buddhist philosophical premise and also favored by many in psychology) , but in the spirit of Camus's Absurdity argument in Myth of Sisyphus, I am not satisfied with doing away one of the variables of the equation itself, so let us see, where this model of self-as-a-deterministic-being leads us to. Now that subject Z remains the same for two iterations of situation A, how can one explain the variance that results in action B at one time and action C at the other. One can again try to dissolve the equation by claiming that there is no unified self in space (earlier argument was that there is no unified self in time- it is a constantly changing in time self) - that is we are not a single self , but made up of many different selves- some conscious, some unconscious etc. Different selves may compete with each other and whoever wins at the moment, directs the show. Again assuming different selves cohabiting the same person doesn't really feel what-it-is like to-be-oneself , and apart from some multiple-personality disorder (DID) this has not been frequently reported; but more importantly . Granting multiple selves to subject Z  again vanishes one of the terms of the equation, and I am not interested, I want to stay and see where my inquiry takes me to.

If the situation is same, the subject is same and a single one, than what explains the within-subject variance? One has to grant unpredictability to a self that was assumed to be deterministic to begin with. One can now take two routes, either resort to the magical mumbo-jumbo of quantum world and indeterminacy and uncertainty; or  stay in the deterministic world but look at complex systems/ chaos theory etc to explain the apparent indeterminacy.  I believe a zombie will prefer the second route and model the self as a complex-system/chaotic self. One could say that the self/ others are still completely determined, but due to an initial 'butterfly flapping wings effect' the self seems or appears to be unpredictable and will continue to remain unpredicatble because of that 'original sin'. The original sin may be how the infant took the first breath, whether he cried or laughed when born; what the time of conception was etc etc. Whatever may be the initial condition that escaped measuring, it leads to an unperdicatble self, a chaotic self that one cannot measure in the present and thus cannot predict in the long term- a self that is as fickle and as perdicatble as the waether.

There are important implications to seeing / modeling the self as a chaotic system. That leads to a diminished sense of agency / responsibility as perhaps there is not much one can do to correct the original sin and thus modify/ change ones long term behavior. This diminished p-consciousness of agency and the consequent differential experiences of sensations/ perceptions should also lead to diminished qualia or what-it-feels-to be-like feeling.  Maybe the zombies do feel really like zombies- mechanical and chaotic- going along the life stream in a mechanical , predetermined manner- seeing all and understanding all, even acting and reacting, but feeling impotent and lifeless, perhaps just fulfilling a role which has been scripted by someone else (the initial butterfly flapping its wings or the original sin).

This is a good point to stop, but I would like to thank Melbren, a reader of this blog, who commented on my last post and asked me if I would re-define , give a new name to Autism spectrum disorders. Thta made me think and somehow led to this post. But first his comment:

Very cool post. And I love your blog. I am trying to think about this particular post in terms of your psychotic spectrum--most specifically as it relates to autism. But I am impeded by an overwhelming feeling that if we have a new spectrum--we'll need new terms. The term "autism" has outgrown its usefulness, don't you think?
For one thing--if we are to use the framework of a psychosis spectrum--I think there will be a lot of people currently diagnosed with autism who are, in fact, organically more biased toward the opposite end of the spectrum. However, such individuals may still have "stereotypies" that we have come to associate with the term "autism."
That being said--if you were appointed "word czar of the day," and, as such, had the authority to scrap all of our conventional terminology and come up with "new and improved" terms that are more in alignment with a psychosis spectrum--what new terms would you choose?


I conceptualize autism as defect whereby people falsely apply a deterministic model (relevant for the world/ non-living things) to the self/others (living things) ; I consider of psychosis as the reverse, whereby one applies an agentic model to the world, thus exhibiting magical thinking etc. Because psychotic spectrum is consptualised in terms of a disability (loss of contact with reality), I would rechristen autism spectrum as the zombie spectrum (loss of contact with agency); of course, If I indeed am the 'word czar of the day' I'll probably rename both as consciousness-orientation (psychotic spectrum)  and reality-orientation (autistic spectrum) and highlight the good aspects of both- shaministic Altered states of consciousness and creativity of schizotypals and the scientific and savantic abilities of the Aspergers. Of course, in a lighter vein, perhaps the autistic spectrum people are 'muggles'  (believers in ordinariness ) who still have to come to terms with the 'magic' (believers in extraordinariness)  of consciousness.
Reblog this post [with Zemanta]

Sphere: Related Content

Thursday, May 28, 2009

How Mood and felt Energy are related to thought variability and speed

There is a recent article by Pronin and Jacobs, on the relationship between mood, thought speed and experience of 'mental motion' that builds up on their previous work.

Let us see how they describe thought speed and variability and what their hypothesis is:


1. The principle of thought speed. Fast thinking, which involves many thoughts per unit time, generally produces positive affect. Slow thinking, which involves few thoughts per unit time, generally produces less positive affect. At the extremes of thought speed, racing thoughts can elicit feelings of mania, and sluggish thoughts can elicit feelings of depression.
2. The principle of thought variability. Varied thinking generally produces positive affect, whereas repetitive thinking generally produces negative affect. This principle is derived in part from the speed principle: when thoughts are repetitive, thought speed (thoughts per unit time) diminishes. At its extremes, repetitive thinking can elicit feelings of depression (or anxiety), and varied thinking can elicit feelings of mania (or reverie).

Let me clarify at the outset that they are aware of the effects of though speed on variability and vice versa; as well as the effects of mood on felt energy and vice versa; thus they know that one can confound the other. Another angle they consider is the relationship between thought speed/variability i.e the form of thought and the contents of thought (whether having emotional salience or neutral) and investigated whether the effects of speed and variability were confounded with though content; they found negative evidence for this inetrcationist view.

Let me also clarify that I differ slightly (based on my interpreation of their data) from their original hypothesis, in the sense that I believe that their data shows that speed affects felt energy and variability affects affect and that the effects of speed on mood may be mediated by the effect of speed on felt energy and similarly the effect of variability on felt energy may be mediated by its effects on mood.

Thus my claim is that:

  1. Thought speed leads to more felt energy. Extremes of 'racing thoughts' leads to the manic feeling of being very energetic (when accompanied with positive mood, this may give rise to feelings of grandiosity- I have the energy to achieve anything), while also may lead to anxiety states (when accompanied with negative affect) in which one cannot really suppress a negative chain of thoughts - one following the other in fast succession, regarding the object of ones anxiety. The counterpart to this the state where thoughts come slowly (writer's block etc) and when accompanied with negative affect, this can easily be viewed as depression.
  2. Thought variability leads to more positive affect: Extremes of 'tangential thoughts' leads to the manic feeling of being in a good mood (when accompanied with high energy , this manifest as feelings of euphoria); while the same tangential thoughts when accompanied by low felt energy may actually be felt as serenity/ calmness/ reverie. The counterpart to this is the state of thoughts that are stuck in a rut - when accompanied with low energy this leads to feelings of depression and sadness.

Thus, to put simply : there are two dimensions one needs to take care of - mood (thought variability) x energy (thought speed) and high and low extremes on these dimensions are all opposites of their counterpart.

Before we move on, I'll let the authors present their other two claims too:
3. The combination principle. Fast, varied thinking prompts elation; slow, repetitive thinking prompts dejection. When speed and variability oppose each other, such that one is low and the other high, individuals’ affective experience will depend on factors including which one of the two factors is more extreme. The psychological state elicited by such combinations can vary apart from its valence, as shown in Figure 1. For example, repetitive thinking can elicit feelings of anxiety rather than depression if that repetitive thinking is rapid. Notably, anxious states generally are more energetic than depressive states. Moreover, just as fast-moving physical objects possess more energy than do identical slower objects, fast thinking involves more energy (e.g., greater wakefulness, arousal, and feelings of energy) than does slow thinking.
4. The content independence principle. Effects of thought speed and variability are independent of the specific nature of thought content. Powerful affective states such as depression and anxiety have been traced to irrational and dysfunctional cognitions (e.g., Beck, 1976). According to the independence principle, effects of mental motion on mood do not require any particular type of thought content.

They review a number of factors and studies that all point to a causal link between thought speed and energy and between thought variability and mood. More importantly they show the independent effects of though speed and variability from the effects of thought content on mood. I'll not go into the details of the studies and experiments they performed, as their article is available freely online and one can read for oneself (it makes for excellent reading); suffice it to say that I believe they are on the right track and have evidence to back their claims.

What are the implications of this:

The speed and repetition of thoughts, we suggest, could be manipulated in order to alter and alleviate some of the mood and energy symptoms of mental disorders. The slow and repetitive aspects of depressive thinking, for example, seem to contribute to the disorder’s affective symptoms (e.g., Ianzito et al., 1974; Judd et al., 1994; Nolen-Hoeksema, 1991; Philipp et al., 1991; Segerstrom et al., 2000). Thus, techniques that are effective in speeding cognition and in breaking the cycle of repetitive thought may be useful in improving the mood and energy levels of depressed patients. The potential of this sort of treatment is suggested by Pronin and Wegner’s (2006) study, in which speeding participants’ cognitions led to improved mood and energy, even when those cognitions were negative, self-referential, and decidedly depressing. It also is suggested by Gortner et al.’s (2006) finding that an expressive writing manipulation that decreased rumination (even while inducing thoughts about an upsetting experience) rendered recurrent depression less likely.

There also is some evidence suggesting that speeding up even low-level cognition may improve mood in clinically depressed patients. In one experiment, Teasdale and Rezin (1978) instructed depressed participants to repeat aloud one of four letters of the alphabet (A, B, C, or D) presented in random order every 1, 2, or 4 s. They found that those participants required to repeat the letters at the fastest rate experienced the most reduction in depressed mood. Similar techniques could be tested for the treatment of other mental illnesses. For example, manipulations might be designed to decrease the mental motion of manic patients, perhaps by introducing repetitive and slow cognitive stimuli. Or, in the case of anxiety disorders, it would be worthwhile to test interventions aimed at inducing slow and varied thought (as opposed to the fast and repetitive thought characteristic of anxiety). The potential effectiveness of such interventions is supported by the fact that mindfulness meditation, which involves slow but varied thinking, can lessen anxiety, stress, and arousal.
 hat tip: Ulterior Motives

ResearchBlogging.org
Pronin, E., & Jacobs, E. (2008). Thought Speed, Mood, and the Experience of Mental Motion Perspectives on Psychological Science, 3 (6), 461-485 DOI: 10.1111/j.1745-6924.2008.00091.x
Pronin, E., & Wegner, D. (2006). Manic Thinking: Independent Effects of Thought Speed and Thought Content on Mood Psychological Science, 17 (9), 807-813 DOI: 10.1111/j.1467-9280.2006.01786.x

Sphere: Related Content

Wednesday, May 27, 2009

Best of Tweets: 27-05-09

Here goes:

  1. Fast, happy, and impulsive I: Speed makes you happy http://ff.im/-35MoD 
  2. Bad drives reactions, Good propels behaviors http://ff.im/-36HFt 
  3. even 'classical' radioactivity is random RT @Wildcat2030: Free Will And Quantum Physics: Less Related Than You Think - http://bit.ly/145bEJ 
  4. co-operation as 'another' feature/ guiding principle of evolution RT @XiXiDu: The Key to Success? http://is.gd/CjEG
  5. RT @mariapage: RT @news_science: Psychologists find that head movement is more important than ... http://cli.gs/zTyZJA #LinkTweet
  6. the improv. nature of web2.0 RT @Wildcat2030: new essay "Wildcat: Jazzing the Beast" The web cultural revolution http://bit.ly/19o2X5
  7. RT @BoraZ: @carlzimmer: .3quarksdaily's new prize for science blogs. Submit url of your favorite blog post: http://tinyurl.com/re3cjp
  8. Encephalon #71: Big Night http://ff.im/-3fHBH
  9.   The Universal Language of Bird Song - Very Short List http://ff.im/-3fIk3  
  10. Welcome to the Stream: The Next Phase of the Web | Twine http://ff.im/-3gaqN
  11. RT @anibalmastobiza: RT: @DoctorZhivago Why We Stare, Even When We Don't Want to: http://bit.ly/IOcx5
  12. RT @Wildcat2030: "In search of the black swans" Mark Buchanan comments on marginal revolutionary ideas in science http://bit.ly/UeosV   

Sphere: Related Content

Tuesday, May 26, 2009

Major conscious and unconscious processes in the brain: part 5: Physical substrates of A-cosnciousness

This is the fifth post in my ongoing series on major conscious and unconscious processes in the brain. For earlier parts, click here.

Today , I would like to point to  a few physical models and theories of consciousness that have been proposed that show that consciousness still resides in the brain, although the neural/ supportive processes may be more esoteric. 

I should forewarn before hand that all the theories involve advanced understanding of brains/ physics/ biochemistry etc and that I do not feel qualified enough to understand/ explain all the different theories in their entirety (or even have a surface understanding of them) ; yet , I believe that there are important underlying patterns and that applying the eight stage model to these approaches will only help us further understand and predict and search in the right directions. The style of this post is similar to the part 3 post on robot minds that delineated the different physical approaches that are used to implement intelligence/ brains in machines.

With that as a background, let us look at the major theoretical approaches to locate consciousness and define its underlying substrates. I could find six different physical hypothesis about consciousness on the Wikipedia page:

  1. * Orch-OR theory
  2. * Electromagnetic theories of consciousness
  3. * Holonomic brain theory
  4. * Quantum mind
  5. * Space-time theories of consciousness
  6. * Simulated Reality

Now let me briefly introduce each of the theories and where they seem to have been most successful; again I believe that though this time visually-normal people are perceiving the elephant, yet they are hooked on to its different aspects and need to bind their perspectives together to arrive at the real nature of the elephant.

1. Orch-OR theory:

The Orch OR theory combines Penrose's hypothesis with respect to the Gödel theorem with Hameroff's hypothesis with respect to microtubules. Together, Penrose and Hameroff have proposed that when condensates in the brain undergo an objective reduction of their wave function, that collapse connects to non-computational decision taking/experience embedded in the geometry of fundamental spacetime.
The theory further proposes that the microtubules both influence and are influenced by the conventional activity at the synapses between neurons. The Orch in Orch OR stands for orchestrated to give the full name of the theory Orchestrated Objective Reduction. Orchestration refers to the hypothetical process by which connective proteins, known as microtubule associated proteins (MAPs) influence or orchestrate the quantum processing of the microtubules.
Hameroff has proposed that condensates in microtubules in one neuron can link with other neurons via gap junctions[6]. In addition to the synaptic connections between brain cells, gap junctions are a different category of connections, where the gap between the cells is sufficiently small for quantum objects to cross it by means of a process known as quantum tunnelling. Hameroff proposes that this tunnelling allows a quantum object, such as the Bose-Einstein condensates mentioned above, to cross into other neurons, and thus extend across a large area of the brain as a single quantum object.
He further postulates that the action of this large-scale quantum feature is the source of the gamma (40 Hz) synchronisation observed in the brain, and sometimes viewed as a correlate of consciousness [7]. In support of the much more limited theory that gap junctions are related to the gamma oscillation, Hameroff quotes a number of studies from recent year.
From the point of view of consciousness theory, an essential feature of Penrose's objective reduction is that the choice of states when objective reduction occurs is selected neither randomly, as are choices following measurement or decoherence, nor completely algorithmically. Rather, states are proposed to be selected by a 'non-computable' influence embedded in the fundamental level of spacetime geometry at the Planck scale.
Penrose claimed that such information is Platonic, representing pure mathematical truth, aesthetic and ethical values. More than two thousand years ago, the Greek philosopher Plato had proposed such pure values and forms, but in an abstract realm. Penrose placed the Platonic realm at the Planck scale. This relates to Penrose's ideas concerning the three worlds: physical, mental, and the Platonic mathematical world. In his theory, the physical world can be seen as the external reality, the mental world as information processing in the brain and the Platonic world as the encryption, measurement, or geometry of fundamental spacetime that is claimed to support non-computational understanding.
To me it seems that Orch OR theory is more suitable for forming platonic representations of objects - that is invariant/ideal perception of an object. This I would relate to the Perceptual aspect of A-consciousness.

2. Electromagnetic theories of consciousness

The electromagnetic field theory of consciousness is a theory that says the electromagnetic field generated by the brain (measurable by ECoG) is the actual carrier of conscious experience.
The starting point for these theories is the fact that every time a neuron fires to generate an action potential and a postsynaptic potential in the next neuron down the line, it also generates a disturbance to the surrounding electromagnetic (EM) field. Information coded in neuron firing patterns is therefore reflected into the brain's EM field. Locating consciousness in the brain's EM field, rather than the neurons, has the advantage of neatly accounting for how information located in millions of neurons scattered throughout the brain can be unified into a single conscious experience (sometimes called the binding problem): the information is unified in the EM field. In this way EM field consciousness can be considered to be 'joined-up information'.
However their generation by synchronous firing is not the only important characteristic of conscious electromagnetic fields — in Pockett's original theory, spatial pattern is the defining feature of a conscious (as opposed to a non-conscious) field.
In McFadden's cemi field theory, the brain's global EM field modifies the electric charges across neural membranes and thereby influences the probability that particular neurons will fire, providing a feed-back loop that drives free will.

To me, the EM filed theories seem to be right on track regarding the fact that the EM filed itself may modify / affect the probabilities of firing of individual neurons and thus lead to free will or sense of agency by in some sense causing some neurons to fire over others. I believe we can model the agency aspect of A-consciousness and find neural substrates of the same in brain, using this approach.

3. Holonomic brain theory:

The holonomic brain theory, originated by psychologist Karl Pribram and initially developed in collaboration with physicist David Bohm, is a model for human cognition that is drastically different from conventionally accepted ideas: Pribram and Bohm posit a model of cognitive function as being guided by a matrix of neurological wave interference patterns situated temporally between holographic Gestalt perception and discrete, affective, quantum vectors derived from reward anticipation potentials.
Pribram was originally struck by the similarity of the hologram idea and Bohm's idea of the implicate order in physics, and contacted him for collaboration. In particular, the fact that information about an image point is distributed throughout the hologram, such that each piece of the hologram contains some information about the entire image, seemed suggestive to Pribram about how the brain could encode memories.
According to Pribram, the tuning of wave frequency in cells of the primary visual cortex plays a role in visual imaging, while such tuning in the auditory system has been well established for decades[citation needed]. Pribram and colleagues also assert that similar tuning occurs in the somatosensory cortex.
Pribram distinguishes between propagative nerve impulses on the one hand, and slow potentials (hyperpolarizations, steep polarizations) that are essentially static. At this temporal interface, he indicates, the wave interferences form holographic patterns.
To me, the holnomic approach seems to be the phenomenon lying between gestalt perception and quantum vectors derived from reward-anticipation potentials or in simple English between the perception and agency components of A-consciousness. this is the Memory aspect of A-consciousness. The use of hologram used to store information as a model, the use of slow waves that are tuned to carry information, the use of this model to explain memory formation (including hyperpolarization etc) all point to the fact that this approach will be most successful in explaining the autobiographical memory that is assited wuith A-cosnciousness.

4. Quantum Mind:

The quantum mind hypothesis proposes that classical mechanics cannot fully explain consciousness and suggests that quantum mechanical phenomena such as quantum entanglement and superposition may play an important part in the brain's function and could form the basis of an explanation of consciousness.
Recent papers by physicist, Gustav Bernroider, have indicated that he thinks that Bohm's implicate-explicate structure can account for the relationship between neural processes and consciousness[7]. In a paper published in 2005 Bernroider elaborated his proposals for the physical basis of this process[8]. The main thrust of his paper was the argument that quantum coherence may be sustained in ion channels for long enough to be relevant for neural processes and the channels could be entangled with surrounding lipids and proteins and with other channels in the same membrane. Ion channels regulate the electrical potential across the axon membrane and thus play a central role in the brain's information processing.
Bernroider uses this recently revealed structure to speculate about the possibility of quantum coherence in the ion channels. Bernroider and co-author Sisir Roy's calculations suggested to them that the behaviour of the ions in the K channel could only be understood at the quantum level. Taking this as their starting point, they then ask whether the structure of the ion channel can be related to logic states. Further calculations lead them to suggest that the K+ ions and the oxygen atoms of the binding pockets are two quantum-entangled sub-systems, which they then equate to a quantum computational mapping. The ions that are destined to be expelled from the channel are proposed to encode information about the state of the oxygen atoms. It is further proposed the separate ion channels could be quantum entangled with one another.

To me, the quantum entanglement (or bond between different phenomenons)and the encoding of information about the state of the system in that entanglement seems all too similar to feelings as information about the emotional/bodily state. Thus, I propose that these quantum entanglements in these ion-channels may be the substrate that give rise to access to the state of the system, thus giving rise to feelings that is the feeling component of A-consciousness i.e access to one's own emotional states.

5. Space-time theories of consciousness:

Space-time theories of consciousness have been advanced by Arthur Eddington, John Smythies and other scientists. The concept was also mentioned by Hermann Weyl who wrote that reality is a "...four-dimensional continuum which is neither 'time' nor 'space'. Only the consciousness that passes on in one portion of this world experiences the detached piece which comes to meet it and passes behind it, as history, that is, as a process that is going forward in time and takes place in space".
In 1953, CD Broad, in common with most authors in this field, proposed that there are two types of time, imaginary time measured in imaginary units (i) and real time measured on the real plane.
It can be seen that for any separation in 3D space there is a time at which the separation in 4D spacetime is zero. Similarly, if another coordinate axis is introduced called 'real time' that changes with imaginary time then historical events can also be no distance from a point. The combination of these result in the possibility of brain activity being at a point as well as being distributed in 3D space and time. This might allow the conscious individual to observe things, including whole movements, as if viewing them from a point.
Alex Green has developed an empirical theory of phenomenal consciousness that proposes that conscious experience can be described as a five-dimensional manifold. As in Broad's hypothesis, space-time can contain vectors of zero length between two points in space and time because of an imaginary time coordinate. A 3D volume of brain activity over a short period of time would have the time extended geometric form of a conscious observation in 5D. Green considers imaginary time to be incompatible with the modern physical description of the world, and proposes that the imaginary time coordinate is a property of the observer and unobserved things (things governed by quantum mechanics), whereas the real time of general relativity is a property of observed things.
These space-time theories of consciousness are highly speculative but have features that their proponents consider attractive: every individual would be unique because they are a space-time path rather than an instantaneous object (i.e., the theories are non-fungible), and also because consciousness is a material thing so direct supervenience would apply. The possibility that conscious experience occupies a short period of time (the specious present) would mean that it can include movements and short words; these would not seem to be possible in a presentist interpretation of experience.
Theories of this type are also suggested by cosmology. The Wheeler-De Witt equation describes the quantum wave function of the universe (or more correctly, the multiverse).

To me, the space-time theories of consciousness that lead to observation/consciousness from a point in the 4d/5d space-time continuum seem to mirror the identity formation function of stage 5.This I relate to evaluation /deliberation aspect of A-consciousness.

6. Simulated Reality
 
In theoretical physics, digital physics holds the basic premise that the entire history of our universe is computable in some sense. The hypothesis was pioneered in Konrad Zuse's book Rechnender Raum (translated by MIT into English as Calculating Space, 1970), which focuses on cellular automata. Juergen Schmidhuber suggested that the universe could be a Turing machine, because there is a very short program that outputs all possible programmes in an asymptotically optimal way. Other proponents include Edward Fredkin, Stephen Wolfram, and Nobel laureate Gerard 't Hooft. They hold that the apparently probabilistic nature of quantum physics is not incompatible with the notion of computability. A quantum version of digital physics has recently been proposed by Seth Lloyd. None of these suggestions has been developed into a workable physical theory.
It can be argued that the use of continua in physics constitutes a possible argument against the simulation of a physical universe. Removing the real numbers and uncountable infinities from physics would counter some of the objections noted above, and at least make computer simulation a possibility. However, digital physics must overcome these objections. For instance, cellular automata would appear to be a poor model for the non-locality of quantum mechanics.
To me the simulation argument is one model of us and the world- i.e we are living in a dream state/ simulation/ digital world where everything is synthetic/ predictable and computable. The alternative view of world as real, analog, continuous world where everything is creative / unpredictable and non-computable. One can , and should have both the models in mind - a simulated reality that is the world and a simulator that is oneself. Jagat mithya, brahma sach. World (simulation) is false, Brahma (creation) is true . Ability to see the world as both a fiction and a reality at the same time, as a fore laid stage and as a creative jazz at the same time leads to this sixth stage of consciousness the A-consciousness of an emergent conscious self that is distinct from mere body/brain. One can see oneself and others as actors acting as per their roles on the world's stage; or as agents co-creating the reality.

That should be enough for today, but I am sure my astute readers will take this a notch further and propose two more theoretical approaches to consciousness and perhaps look for their neural substrates basde on teh remianing tow stages and componenets of A-consciousness..

Sphere: Related Content

Monday, May 25, 2009

Major conscious and unconscious processes in the brain: part 4: the easy problem of A-consciousness

This is the part 4 of the multi-part series on conscious and unconscious processes in the brain.


I'll like to start with a quote from the Mundaka Upanishads:

Two birds, inseparable friends, cling to the same tree. One of them eats the sweet fruit, the other looks on without eating.


On the same tree man sits grieving, immersed, bewildered, by his own impotence. But when he sees the other lord contented and knows his glory, then his grief passes away.


Today I plan to delineate the major conscious processes in the brain, without bothering with their neural correlates or how they are related to unconscious processes that I have delineated earlier. Also I'll be restricting the discussion mostly to the easy problem of Access or A- consciousness.  leaving the hard problem of phenomenal or P-consciousness for later.

I'll first like to quote a definition of consciousness form Baars:

The contents of consciousness include the immediate perceptual world; inner speech and visual imagery; the fleeting present and its fading traces in immediate memory; bodily feelings like pleasure, pain, and excitement; surges of feeling; autobiographical events when they are remembered; clear and immediate intentions, expectations and actions; explicit beliefs about oneself and the world; and concepts that are abstract but focal. In spite of decades of behaviouristic avoidance, few would quarrel with this list today.

Next I would like to list the subsystems identified by Charles T tart that are involved in consciousness:

  • EXTEROCEPTION (sensing the external world)
  • INTEROCEPTION (sensing the body)
  • INPUT-PROCESSING (seeing meaningful stimuli)
  • EMOTIONS
  • MEMORY
  • SPACE/TIME SENSE
  • SENSE OF IDENTITY
  • EVALUATION AND DECISION -MAKING
  • MOTOR OUTPUT
  • SUBCONSCIOUS


With this background, let me delineate the major conscious processes/ systems that make up the A-consciousness as per me:-

  1. Perceptual system: Once the spotlight of attention is available, it can be used to bring into focus the unconscious input representations that the brain is creating.  Thus a system may evolve that has access to information regarding the sensations that are being processed or in other words that perceives and is conscious of what is being sensed. To perceive is to have access to ones sensations.  In Tarts model , it is the input-processing module  that 'sees' meaningful stimuli and ignores the rest / hides them from second-order representation. This is Baars immediate perceptual world.
  2. Agency system: The spotlight of attention can also bring into foreground the unconscious urges that propel movement. This access to information regarding how and why we move gives rise to the emergence of A-consciousness of will/ volition/agency. To will is to have access to ones action-causes. In tarts model , it is the motor output module that enables sense of voluntary movement. In Baars definition it is clear and immediate intentions, expectations and actions.
  3. Memory system:  The spotlight of attention may also bring into focus past learning. This access to information regarding past unconscious learning gives rise to A-consciousness of remembering/ recognizing. To remember is to have access to past learning. The Tart subsystem for the same is Memory and Baars definition is autobiographical events when they are remembered. 
  4. Feeling (emotional/ mood) system: The spotlight of attention may also highlight the emotional state of the organism. An information about one's own emotional state gives rise to the A-consciousness of feelings that have an emotional tone/ mood associated. To feel is to have access to ones emotional state. The emotions system of Tart and Baars bodily feelings like pleasure, pain, and excitement; surges of feeling relate to this.
  5. Deliberation/ reasoning/thought system: The spotlight of attention may also highlight the decisional and evaluative unconscious processes that the organism indulges in. An information about which values guided decision can lead to a reasoning module that justifies the decisions and an A-consciousness of introspection. To think is to have access to ones own deliberation and evaluative process. Tarts evaluative and decision making module is for the same. Baars definition may be enhanced to include intorspection i.e access to thoughts and thinking (remember Descartes dictum of I think therefore I am. ) as part of consciousness.
  6. Modeling system that can differentiate and perceive dualism: The spotlight of attention may highlight the dual properties of the world (deterministic and chaotic ). An information regarding the fact that two contradictory models of the world can both be true at the same time, leads to modeling of oneslf that is different from the world giving rise to the difference between 'this' and 'that' and giving rise to the sense of self. One models both the self and the world based on principles/ subsystems of extereocpetion and interoception and this give rise to A-consciousness of beliefs about the self and the world. To believe is to have access to one's model of something. One has access to a self/ subjectivity different from world and defined by interoceptive senses ; and a world/ reality different from self defined by exterioceptive senses. The interocpetive and exteroceptive subsystems of  Tart and Baars  explicit beliefs about oneself and the world are relevant here. This system give rise to the concept of a subjective person or self.
  7. Language system that can report on subjective contents and propositions. The spotlight of awareness may  verbalize the unconscious communicative intents and propositions giving rise to access to inner speech and enabling overt language and reporting capabilities. To verbally report is to have access to the underlying narrative that one wants to communicate and that one is creating/confabulating. This narrative and story-telling capability should also in my view lead to the A-consciousness of the stream of consciousness. This would be implemented most probably by Tart's unconscious and space/time sense modules and relates to Baars the fleeting present and its fading traces in immediate memory- a sense of an ongoing stream of consciousness. To have a stream of consciousness is to have access to one's inner narrative.
  8. Awareness system that can bring into focal awareness the different conscious process that are seen as  coherent. : the spotlight of attention can also be turned upon itself- an information about what all processes make a coherent whole and are thus being attended and amplified gives rise to a sense of self-identity that is stable across time and  unified in space. To be aware is to have access to what one is attending or focusing on or is 'conscious' of. Tarts Sense of identity subsystem and Baars concepts that are abstract but focal relate to this. Once available the spotlight of awareness opens the floodgates of phenomenal or P-consciousness or experience in the here-and-now of qualia that are invariant and experiential in  nature. That 'feeling of what it means to be' of course is the subject matter for another day and another post!

Sphere: Related Content

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.

Sphere: Related Content

Saturday, May 23, 2009

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!

Sphere: Related Content

Friday, May 22, 2009

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. 

Sphere: Related Content

Wednesday, May 20, 2009

Best of Tweets: 20-05-09

I am starting an experimental new feature today called Best of Tweets. Many other bloggers do weekly link fests and I had somehow refrained form doing one myself. Using twitter, I am able to share many more links that I find interesting instantly , but I know that many of you are not on twitter; so perhaps a weekly best of tweets post that aggregates the best of my tweets for the past week may be useful to the mouse trap blog readers. Do tell me via comments whether you find this useful.Remember that this is a manually compiled by me list of best of tweets and is not auto generated, so I am putting some additional efforts here.

Without further ado, here is the best of tweets for week ending 20-05-09:

  1. RT @Wildcat2030: In defense of distraction--it's not a bug, it's a feature of a new techno-nomadic culture. (via @LynJ) http://bit.ly/sYwcl
  2. Debates on free will / perchance or predetermined / now silence reigns, courtesy free won't #haiku #scaiku (ver 2) #philosophy (for the background of this tweet go read the 4 way convesration I had on twitter on free-will yesterday)
  3. I believe in a libertarian free will concept and thus found the recent Nature article based on randomness in... re: http://ff.im/1Zo2A
  4. a 5 part npr series on brain/spirituality RT @kdwashburn: Great interactive graphic on the brain and spirituality: http://tr.im/lI7F
  5. RT @kdwashburn: "reading someone else's attention involves the same brain circuits that control one's own attention" http://tr.im/lIoZ 
  6. Yes! 50 Scientifically Proven Ways to Be Persuasive http://ff.im/-30dO4
  7. Narrative gravity /go spin a yarn/define yourself .http://bit.ly/14h8sX via @LeadonYoung: http://bit.ly/aTo0e & http://bit.ly/13Qqto #scaiku 
  8. Creativity ,esp. musical / 'a seething cauldron of ideas'/ Jonah peeps in your brain : http://bit.ly/leSwf : #scaiku #haiku #science
  9.  Triune Ethics: On Neurobiology and Multiple Moralities « Neuroanthropology http://ff.im/-2Vui8
  10. Your will is free / not everything is a reaction/ behold the fly acting random! http://bit.ly/hzBGh #scaiku #science #haiku #cognitive 
  11. Depression and Mania / which one comes first / a serpent eating its tail ? : http://bit.ly/18ycU0 #scaiku #science #haiku
  12. psychosis or a dream/ hard to tell/an overactive default network : http://ff.im/-2QNny #scaiku #haiku #science
  13. "We can’t control the world, but we can control how we think about it": Mischel . Sounds a lot like Viktor Frankl. http://bit.ly/118zfl
  14. via @anibalmastobiza : cool genomic imprinting paper that predates Badcock/Crespi's work on Autism/Psychosis http://bit.ly/o8ppS

Sphere: Related Content

Attention allocation / Same as action selection/ New insight on ADHD #haiku #scaiku

The title of my above post is a scaiku (scientific haiku in 140 chars on twitter) that I posted last night on twitter.I am using this title as the inspiration for this post is twitter itself.

Last night, after a hard day full of tweeting (yes tweeting and keeping up with all the friends' tweets is a lot of hard work- go check the 4-way conversation I had on cosnsciousness and free will), I was not able to relax myself, but found myself in a constant state of distraction and restlessness, and getting up in middle of night to update my status.  Of course I have heard of twitter addiction and would rubbish that off; but I could not rubbish off the unique demands on attention and juggling that twittering makes on you. First off, you need to read a lot of tweets and find the needle in the haystack- the tweets that need to be retweeted/replied to and ignore/forget the rest of them as soon as possible. Secondly, I at least, juggle constantly between windows and tabs of tweetdeck and other application trying to do optimal scavenging (feeding off good content tweeted by others) and foraging (finding a good tweetable link myself).

So to sum up, I found that twitter had taxed, at least yesterday, my attentional system- leading to a habitual distractibility and also my motor system hat had constantly flitted between open windows and tabs leading to a habitual distractibility. I am sure that was a very short term and temporary phenomenon, but that set me thinking  I have already devoted an entire post to how attention allocation and action selection may be similar and have drawn many parallels. The fundamental problem in  both the cases is to choose an action/ stimuli to attend to, that can maximize the rewards from the world/ predictability of the world.  At any given time, there are many more stimuli to attend to and acts to indulge in than are the attentional/intentional resources required for the same and thus one has to choose between alternatives. Mathematicaly, different acts have different probabilities associated with them that they would lead to a rewarding state- this wave function needs to be collapsed such that only one act is actually intended. One way to do is my maximizing Utility (ExV) associated with different acts and choosing the maximal one always; another solution is to randomly choose an act from the given set  in accordance with  the probability distribution  that is a function of their utilities.I believe that instead of maximizers most of us are staisficers and especially in time-sensitive decisions go for an undeliberate choice that does'nt actually maximize the utility over all possible behavioral acts, but choses one of them randomly/probabilistically as per their prior known probabilities of rewards. Thus, we can be both maximizers as well as satisficers and which system we engage depends both on situational factors as well as our personality tendencies/ habits.

Anyway that was a lot of digression from the main line of argument. To continue with the digression for some more time, if one extends the analogy to attending to stimuli, on can either attend to stimuli that leads to greatest predictability (P= ExR) ;  or one can attend to a stimuli from a given set in accordance with a probability distribution that is a function of their prior predictabilities. again I haven't even got into Bayesian models where thing should get more complicated; suffice it to note for now that both attention-allocation and action-selection involve choosing an act / stimuli from a set.

A look at the Utility function of acts (U=ExV) and  Predictability function of stimuli (P = ExR) , immediately outlines the importance of dopamine in the above choosing mechanism as it encodes both (reward) expectancy as well as incentive salience/Value for acts;  on the attentional side of things, it should encode  both the strength of conditioned association (E) as well as (stimuli) Relevance for minimizing surprise. As such it should detect novelty in stimuli that can indicate that things have changed and the internal model needs updating. 

I also talked in my last post about a general energy level that leads to more propensity to indulge in operant acts and a general arousal level that leads to more propensity to attend to external stimuli. Today I want to elaborate on that concept using ADHD as a guide - ADHD has primarily two varieties (and in most general case both co-exist) - the inattentive type and the hyperactive-impulsive type. In the inattentive type, one is easily distracted or to put in my conceptualization - has a high baseline arousal leading to more frequent monitoring to the world/ external stimuli . The attention-reallocation happens faster than controls and may be triggered by irrelevant stimuli too. In the hyperactive-impulsive type,  one is overly active and impulsive or to put in mu conceptualization- has a high baseline energy level leading to more frequent shifts in activities and possibly triggering unvalued acts (impulses that are not really rewarding) .

It is important to note that dopamine and dopamine mediated regions like smaller PFC, cerebellum and basal ganglia, dopamine related genes like DAT1 and DRD4  and Ritalin that works primarily on dopamine have been implicated in ADHD.  All the above points to a dopamine signalling aberration in ADHD. Once one embraces the overarching framework of action-allocation and action-selection as similar in nature and possibly involving dopamine neurons, it is easy to see why ADHD children should have both hyperactive-impulsive and inattentive syndromes and subgroups.

Sphere: Related Content