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• Alfredo Pereira Jr

  22 April 2008 | 14:09

  Dear Bernard:

  I have some preliminary comments:

  1) There is no ‘a priori’ reason why conscious activity would require
  more energy than unconscious activity, since the unconscious ones also
  have biological functions (some of them probably more crucial for
  survival than consciousness). A difference of 6% (between conscious
  and unconscious activity) is meaningful, and also theoretically important, if we can identify how this energy is used;

  2) EEG recordings make use of filters that highlight the traces that the
  researcher wants to put in evidence. In most cases what is looked for
  is the pattern (e.g.coherent patterns) instead of gross
  thermodynamical values;

  3) Most fMRI cognitive neuroscientific experiments use the subtraction
  method, which may be considered as similar to the “contrastive
  analysis” currently used with ERP/EEG. Unconscious activity is
  substracted from conscious activity. This usage may help to explain
  why fMRI results are relevant to consciousness research;

  4) There are deeper issues concerning the relation of brain physiology
  with consciousness. One of them is the role of inhibitory activity
  (please check our discussion here). In principle, inhibitory
  activity should spend more energy than excitatory, since inhibition
  involves both the excitation of inhibitory neurons and the
  hyperpolarization of excitatory ones. Physically speaking,
  hyperpolarization refers to electrical fields (difference of potential
  between the interior and the exterior of the neuron) with greater
  magnitude than the fields corresponding to excitation (depolarization
  processes)!

  5) The only way to discard inhibitory activity and subthreshold
  oscillations is making single unit recordings selective for axonal
  activity (firing); however,

  6) It is not clear that conscious processing correlates with firing
  activity. Possibly, increase of firing is a consequence of the
  activities that generate consciousness (coherent EPSPs in a large cell
  assembly), not the cause of them. However, neuronal firing activate
  EPSPs in other neurons, and this sequence of activations must be
  related to the “stream of consciousness” and the transition from
  conscious activity to overt behavior.

  Considering all these complexities, a difference of 6% is really interesting!

  Best

  Alfredo

• Bernard Baars

  24 April 2008 | 04:39

  I take your points, Alfredo. I didn’t think the energetics of conscious and unconscious brain events were all that interesting until recently, when I started to look at Walter Freeman’s work in detail. Gerald Edelman also talks about “far-from-equilibrium” functioning of the brain. We’re preparing for a small workshop of very interesting people at U Memphis, called “Consciousness, Brain Rhythms, and the Action-Perception Cycle.” organized by Stan Franklin and myself. It’s at http://ccrg.cs.memphis.edu/brain-rhythms-workshop.html

  There is a little swarm of recent papers on brain rhythms and conscious (unconscious) functions, with some very provocative results. See the workshop website, and papers at my wiki site, www.bernardbaars.pbwiki.com

  One widespread notion seems to be that synchrony/ coherence /phase locking etc. is a better index of regional interactions in cortex than amplitude, or perhaps even microlevel neuronal firing patterns. Some of the work has been done with ECoG (electrocorticogram), with electrodes on top of the cortex, or other intracranial recordings, which get around the spatial smearing and EMG artifacts of scalp EEG. There are also volume conduction and possibly cranial resonance artifacts. But when you’re pretty sure you’re eliminating all of that, you get these remarkable correlations of theta, alpha, beta, gamma, and even delta band synchrony with conscious and unconscious functions.

  So this is intriguing. I hope to learn more in a couple of weeks, when the Memphis workshop takes place (May 3-4). Perhaps we can post some of the papers and powerpoints for discussion here.

  Bernard

• Peter Cariani

  24 April 2008 | 19:33

  I have many criticisms of the assumptions and reasoning in the paper—
  on one level, I commend the authors for trying to propose and test a basic hypothesis, on the other hand, though this may be a good example of how imaging technologies have actually degraded our thinking about the nature of neuronal processing.

  A pervasive problem is that many people confuse what they observe of neuronal activity through their (imaging, EEG gross potential) methods with those aspects of neuronal activity that are/may be involved with informational function and consciousness. Depending on the nature of the underlying neural codes and computations, some aspects of neuronal response (gross levels of neuronal “activation”, “oscillatory” behavior) may or may not be directly related to conscious awareness or its contents. In his 2001 book The New Phrenology, William Uttal pointed out how imaging techniques bias the interpretation of neuronal activity toward localizationist conceptions of neuronal information processing.

  On the current scene it is common to describe the neuronal correlates of consciousness in terms of enhanced activation of particular brain regions, as if this is sufficient for awareness and its contents. Anyone who has seriously thought about the neural coding problem knows that there are many possible ways to represent information and that many of these do not involve increases in firing rates per se, but different patterns of correlated activity. In response to an excellent paper on anesthesia and neuronal activity by Alkire et al that proposed an “activity suppression” model for the abolition of consciousness, I argued that the neuronal requisites for conscious awareness might instead involve coherently patterned neuronal activity, such that some anesthetics might abolish consciousness by “scrambling” neuronal signal rather than suppressing them. I called this kind of account a “process-coherence” theory of consciousness.
  (see Cariani, P. Consciousness and Cognition (2000) 9:387-395 Anesthesia, Neural Information Processing, and Conscious Awareness).

  In that paper I quoted Mary Brazier, who wrote several books on neurophysiology and anesthesia and who was head of Anesthesiology at Mass. General Hospital in the 1950’s:

  “This is perhaps the place to note that neurophysiology has now emerged from the era when the principal frame of reference was based on an energy system. Interest is now focused on the nervous system as a communication system and on the ability of nerve impulses to travel their normal routes. To draw a parallel from the vacuum tube, it is not the energy of the filament current that interests us, but the ‘message’ on the grid.” Brazier (1954), p. 169.

  So the thinking in this current paper, with its assumptions of a scarcity-driven neural energy economy and the lack of halfway-sophisticated neural coding models, sets us back half a century!

  I also quoted H. H. Jasper (1965):
  “It has been postulated that conduction of impulses from cortical sensory receiving areas to a centrencephalic system of neurons may be critical for conscious awareness. This may well be true, but perhaps only followng extensive cortical elaboration, re-enforced by the activating influences of nonspecific afferents from the brain stem upon widespread cortical and subcortical structures. The fact that chloralose anesthesia, for example, enhances widespread conduction of afferent volleys in sensory receiving areas, as well as in the “non specific” portions of thalamus and brain stem, even though the animal appears to be unconscious, shows that simple conduction of afferent volleys to the “centrencephalic system” is not sufficient for conscious awareness to occur. This is probably analogous to the unconscious state resulting from excessive epileptic bombardment producing a blockade of integrative functions of the systems critical to conscious awareness. This implies that a certain level of integration, rather than simple activation of certain neural systems, is critical to the existence of conscious awareness. The fact that chloralose also blocks the release of ACH in the cortex suggests that critical chemical reactions in only certain classes of cortical neurons may be a necessary accompaniment of the type of activation necessary to translate information processing into conscious awareness. It seems clear, at any rate, that marked changes do occur in cortical activity in conscious as opposed to unconscious states of the brain, and that the importance of the centrecephalic or reticular system of the brain stem probably lies not in its importance as a localization of conscious processes, but in its remarkable and widespread interactions with more specialized neuronal systems, somehow determining which of these functional systems is to gain momentary predominance in the on-going sequence of conscious awareness. It would seem to be wrong to call this a non-specific function in the broad sense of the word, for in neuronal systems, what could be more specific than the complex reactions which provide that increment of integrated activation necessary for conscious awareness.” Jaspers(1965), pp. 272-273. Brain mechanisms and states of consciousness. In J. C. Eccles (Ed.), Brain and conscious experience (pp. 256– 282). New York: Springer-Verlag.

  Beyond problems with neural coding assumptions, there are some basic problems with optimality arguments in biology, neuroscience, and psychology.
  First off, everyone and his brother wants to believe that neural activity and neural codes are some kind of evolutionarily-driven optimum, either for energy consumption or for Shannonian information-carrying capacity.
  But the reasoning is highly, highly prone to error if you don’t already understand how the system works (we are still v. far from this at the cortical level) and you don’t have a very clear grasp of the environmental structure, selective pressures, and structure-function alternatives that sensory systems face.

  I am very skeptical of both energy- and info-optimization claims, which appear to me to be based on post-hoc adaptationist just-so stories. It’s not that I am against adaptive optimality or selective pressure—what I am against is this kind of bad evolutionary psychology theorizing, which doesn’t ever critically examine its assumptions or consider alternative explanations.

  If anything, complex, multicellular animals operate very far from thermodynamic equilibrium (warm-blooded creatures even more so, and flying animals even more so)—maybe there are some animals whose harsh environments so constrain their metabolic needs that their nervous systems require drastic optimization for limiting energy use, but these are probably exceptions rather than rules…...

  (a way to test the energy minimization hypothesis is to look at related species that have drastically different energy availability and see if their nervous systems show corresponding changes….). Perhaps a more reasonable energy-conservation hypothesis would be that animals under these constraints tend to sleep more (but when they are awake, their nervous systems operate pretty much like other animals). [Recently there was a good evolutionary psychology study of monkeys with and without good color vision that related the difference in species to the presence of predatory snakes in their habitats – here is a testable and very reasonable hypothesis].

  I think, alternatively, that nervous systems are adapted to perform reliably under a very wide range of environmental conditions, and to do this they require a great deal of ongoing endogenous activity. In the absence of sound, in the cat auditory nerve, 2/3 of neurons (i.e. 20,000 on each side) have spontaneous firing rates of 20-200 spikes/second. What are they doing? IMHO, they are all decorrelated in their firing times, so that if an acoustic wavefront comes through, there will be a significant fraction of the population in recovery, which then makes it possible to encode other events that rapidly follow in the wake of the first wave. Is this very efficient? No, probably not. Is it reliable under a huge range of situations? You bet it is. Is high spontaneous activity a phyletically-broad feature of auditory system design? I would bet so, but I would want to check that assumption. Certainly for mammals it is.

  What is missing here is the notion that brains are energetically-degenerate systems, in which patterns of neuronal activity rather than molar amounts of it steer experience, thought, and behavior.

  The new imaging technologies force people to pay attention to imagined changes in firing rates, but what changes most is the pattern of neural activity, not the molar quantities involved. This is why BOLD signal differences of 1 or 2 or 4% are so unimpressive on their face—huge changes in firing patterns are occurring without correspondingly huge changes in overall firing rates. It is true that some neurons fire more often, more intense stimuli activate wider ranges of cortical territory above resting levels, and stimuli that have high semantic and pragmatic/hedonic saliency will drive more activity in more different neuronal populations, but in the great scheme of body metabolism, these differences are not at all impressive. I wish that they were—if so, thinking intensely (vs. muscular exercise) would be a great strategy for losing weight! (As I’ve learned the hard way, it isn’t.)

  As irritated as I am with their neural coding assumptions (or lack thereof), I think their results are consistent with the general idea that it is patterns of activity that are sustained in reverberating circuits (what I call “signal regeneration”) that constitute the contents of working memory/global & local workspaces at any given time. I think that a requisite signal to noise ratio is needed for a given signal to evoke a change in the contents of experience, so that there is a buildup process that goes on. But a regenerating pattern need not necessarily mean that more neurons are firing more often—it can mean that they are firing more coherently (in this case , what I mean by “coherence” is that the same neuronal spike patterns are being produced in more neurons, such that the proportion of pattern-correlated activity is higher).

  IMHO, the section on skin vibration detection leaves a great deal to be desired. Decades ago, Mountcastle and Werner showed that the peripheral code for flutter-vibration is based on interspike intervals, much as in the auditory nerve. I am fairly certain that the interval information for flutter (low frequencies < 50 Hz) is available at the cortical level. I have not kept track of the cortical flutter-vibration coding literature, so it is hard to evaluate whether their coding model is at all well-informed or reasonable (e.g. one should also be able to see spike patterns corresponding to 10 vs. 20 Hz flutter, but it is quite possible that nobody in that field is looking into this possibility). I don’t quite see the point of the example that they give of detecting either similar or different vibration rates—it’s not as if the stimuli are subliminal until a frequency change has occurred (or is it?). (How does this relate to consciousness per se, A-A vs. A-B?) In any case the observed-inferred effect is small (0.6% change in energy) and one wonders how significant this is and also whether the effect would stand up to stress testing.

  The auditory example is really quite shaky—one would really want to scrutinize how they decided to include/exclude single units from their samples for use in estimating avg firing rates (in the literature, about half of auditory cortical neurons do not respond to sound; half of those that do have nonmonotonic rate-level functions; there will be attentional effects, and lots of other complicating factors). Again the energy effect is small. And again I believe (and I could be wrong) it is the rhythmic pattern of activity, not firing rates, which is likely to encode the perceptual difference of galloping vs. isochronous rhythm. So here too, it’s likely to be mostly not the amount of firing, but the pattern of spiking ….. I know people right now who are investigating this – maybe a more specific explanation is on its way.

  —Peter Cariani, 4/24/2008

• Alfredo Pereira Jr

  24 April 2008 | 22:20

  Dear Bernard and Peter:

  We three agree that conscious processing is based on “coherently patterned neuronal activity”, as Peter wrote. However, I suspect that many respectable neuroscientists still believe that it involves a gross increase in firing rates. This is the assumption made in the Schölvinck et al. paper.
  The authors make a criticism of BOLD fMRI, because they believe that conscious processing is more related to neuron firing than to post-synaptic potentials (in this regard, it is very interesting to note that, in the beginning of the paper, they discard LTP-related processes, as Nitric Oxide release and activation of Arachidonic Acid pathways, as contributing to conscious processing – they attribute to these processes only an increase in blood flow).
  Peter also relates conscious processing with axonal activity, but he focuses on the patterns of firing while the paper authors consider that the amplitude of electric fields is more relevant.
  As a proponent of the thesis that conscious processing is based on post-synaptic activity (EPSPs and IPSPs) I agree with Peter´s criticism of the paper, but not for the same reasons that motivated him.

  Best

  Alfredo

• chris lofting

  25 April 2008 | 03:41

  The general focus on conservation of energy covers the extraction of essential elements and so DIFFERENCE to aggrgate such into a pool of SAMENESS that is used at the instincts/habits level of stimulus-response as compared to stimulus-considered_response.

  Brain oscillations bring this out in that inter-hemisphere oscillations cover the new/complex only; simple/known data elicits limited intra-hemisphere dynamics that reflect energy conservation.

  From neural level the indiction is ‘context first’ that sets down SAMENESS and within that operates updates in the form of DIFFERENCES - this dynmic being, overall, energy conserving.

  Added to that are differences in axonal diametres covering band-width issues and so allowance for fast, motor activity, dynamics through wide bandwith channels as compared to small diametre neurons for low level, long term, processing.

  Since consciousness presents as an agent of mediation, so the more unconscious an action the more ‘determined’ the action, the more instinct/habit driven. Consciousness acts to regulate instinctive, inappropriate behaviours through its high differention powers and so higher precision in detecting local differences not identifiable by instincts/habits activities.

  Thus the symmetry of instincts/habits is distorted or even broken by consciousness as consciousness can also refine/create symmetries. Behind all of this is energy conservation as a basic for a life form lining in a thermodynamic universe.

• Alfredo Pereira Jr

  25 April 2008 | 09:34

  Dear Chris:

  I can grasp what you are saying but, when possible, I ask you to make more use of neuroscientific vocabulary, such as “habituation” for the formation of habits; “baseline” for brain activity shaped by previous habits; “sensitization” for a difference that makes a difference, etc.

  Regading thermodynamics, brain energy dynamics is very complex since – as Peter pointed – living systems are considered to be far from equilibrium systems. Besides the constraint of energy conservation, there are two other relevant factors:
  A) a flux of free energy (in the brain, glucose supply) that drives the system towards low entropy states, and in opposition
  B) the second law, that drives the system towards higher entropy states.
  The result of both tendencies is expressed by the “minimum entropy production” principle, which is a very complex issue that I am not able to describe accurately here.

  Best

  Alfredo

• chris lofting

  25 April 2008 | 10:37

  Hi Alfredo, you wrote:

  “Regading thermodynamics, brain energy dynamics is very complex since – as Peter pointed – living systems are considered to be far from equilibrium systems.”

  IMHO this form of thinking by Peter is limited – we are dealing with hierarchy and so (a) a repetition of a pattern within a level and (b) the repetition ‘across’ or ‘up’ levels. Thus the relationships WITHIN a level span the far-from-equilibrium/equilibrium dimension. BUT so does the relationship ACROSS levels, in particular to lower levels is ALSO that of ‘far-from’/equilibrium.

  There is a ground state at the macro level (general system etc) and the micro levels (each level within levels of the hierarchy). We then have to map out the different forms of hierarchy, the nested (web/network like) and the non-nested (pyramid/tree like). The non-nested is high energy and takes care of differences etc.

  As the neurology develops so hierarchy is formed from self-referencing, each level such derived has a bandwidth higher than that from which it has emerged but at the same time has the grading of high differentiations to low.

  We see this in the neuron (axon pulse precision, FM, to dendrites wave precision, AM) and all the way ‘up’ to the hemispheres of the neocortex (left in most is more “FM”, right in most is more “AM” – its pulses and waves all the way. Thus the language of the neuron is of wavelengths, amplitudes, and frequencies.

  The PRECISION aspect covers sampling rates, from high rates for differentiating to lower rates in integrating (where we conserve energy through generalising into instincts/habits where habits reflect instinct creation in realtime i.e. the lifetime of the individual rather than spread over generations)

  So Peter’s assertion is ‘simplistic’, too single context, single level, or no more than two dimensional in thinking; we need to focus on higher levels to grasp consciousness etc.

  You wrote:

  ” Besides the constraint of energy conservation, there are two other relevant factors:
  A) a flux of free energy (in the brain, glucose supply) that drives the system towards low entropy states, and in opposition
  B) the second law, that drives the system towards higher entropy states.
  The result of both tendencies is expressed by the “minimum entropy production” principle, which is a very complex issue that I am not able to describe accurately here.”

  What covered here is the same dynamics covered in the far-from-equ/equ focus; self-reference and you get a dimension of categories covering the dynamics of low entropy drives and high entropy drives.

  What we are dealing with at ALL scales, within and between, is what our brains ‘allow’ us to see – patterns of anti-symmetry/symmetry and a mediation system (asymmetric) managing it all. It does not matter where you look, you will see these patterns manifest in various degrees depending on local contexts.

  The control focus increases as we move ‘up’ hierarchy and so move from a bottom-up to a top-down position, each level of development increases choices available in behaviour and so increases prospects of starting to behave top-down, i.e. a role of governance.

  The realm of the anti-symmetric is more parts focused, high energy, very fast (high bandwidth, high sample rates but LOCAL context) and very precise and in being so highly differentiating and so entropy reducing – order for US. Going the other way is energy conserving over the long run to a level of no highs, no lows, and so order as far as the universe is concerned! ;-)

  Chris.

• Peter Cariani

  25 April 2008 | 15:50

  Chris,

  I appreciate the perspective of a hierarchy of levels in the nervous system, although, perhaps the often neglected notion of a heterarchy of competing and cooperating ensembles of neurons is at least as powerful and applicable a concept. Thus far I fail to see, however, how the introduction of levels of organization changes the nature of the optimality arguments.

  I was wondering which assertion of mine you find “simplistic”.

  Part of my point is that very few of these arguments for energy- and Shannonian-information- optimality ever marshall any convincing empirical evidence that the organization of neuronal information processing is in some sense an optimal one. Can you think of any concrete, empirical evidence for this? Instead this is taken as an article of faith that doesn’t need proving. Optimality assumptions are very appealing to mathematicians and physicists—they drastically simplify formal treatments of physical problems.

  OK, maybe neural functional organization is an optimum in some sense (I’m not averse to the general idea), but what is exactly is being optimized is the real question. These arguments will be very prone to error until we have a firm grasp on the precise nature of information processing in the brain, SUCH THAT WE KNOW EXACTLY WHAT IS BEING OPTIMIZED. In other words, we need to solve the neural coding problem before many of these questions can be effectively resolved. Until we do this, we are mostly groping in the dark. In the meantime, it is important to make the best of what knowledge we have, and to keep as many ideas on the table as possible.

  In this respect, I think the paper is very positive in proposing a hypothesis about energy economy, and reporting their findings even when these contradict their starting assumptions. I just want their notions of neural codes and computations to be more sophisticated, variegated, and nuanced than they seem to be on their face.

  Despite my arguments against optimality, I AM an optimist—these problems are tractable if enough scientists are allowed to address them. I do think that the neuroscience of consciousness is making steady progress, both experimentally and theoretically, and that in our lifetimes we will reach a reasonable understanding of the nature of the neuronal basis of conscious awareness.

  Peter Cariani 4/25/2008

• Avi Peled

  25 April 2008 | 19:45

  Schizophrenia is a disorder of consciousness; does the theory of consciousness propose any idea about how this disorder maybe cured?

• chris lofting

  26 April 2008 | 04:26

  Hi Peter,

  you wrote in your original post:

  “First off, everyone and his brother wants to believe that neural activity and neural codes are some kind of evolutionarily-driven optimum, either for energy consumption or for Shannonian information-carrying capacity.
  But the reasoning is highly, highly prone to error if you don’t already understand how the system works (we are still v. far from this at the cortical level) and you don’t have a very clear grasp of the environmental structure, selective pressures, and structure-function alternatives that sensory systems face.”

  and then in your reply to me:

  “Part of my point is that very few of these arguments for energy- and Shannonian-information- optimality ever marshall any convincing empirical evidence that the organization of neuronal information processing is in some sense an optimal one”

  and

  “OK, maybe neural functional organization is an optimum in some sense (I’m not averse to the general idea), but what is exactly is being optimized is the real question. These arguments will be very prone to error until we have a firm grasp on the precise nature of information processing in the brain, SUCH THAT WE KNOW EXACTLY WHAT IS BEING OPTIMIZED. In other words, we need to solve the neural coding problem before many of these questions can be effectively resolved.”

  Firstly I notice a focus ‘shannonian’ information. This is half of the whole that is made up of the dichotomy of Shannon/Gabor where THAT perspective fits better with the general architecture of brain and its dynamics in information processing:

  Shannon – anti-symmetric, local, discrete
  Gabor – symmetric, non-local, continuous

  If we focus on information spanning all hierarchy (something you did not cover in your original post by acknowledged the need for consideration of such in your answer to me) then consideration of SAMENESS that is output by the brain is a manifestation of common ground within the neurology that is then amplified or damped or even expunged to give us the differences in expressions.

  What is being optimised are patterns derived from the sensory systems and translated into patterns of differentiating/integrating in the form of frequencies, wavelengths, and amplitudes. What this process does, or more so an artifact of such and so something exploitable, is give us categories usable for seeding communications of anything in the dealings of the life form and its context.

  At the neuron level we cover the FM clarity of axonial dynamics (and so the discrete, the pulse, focus) and the AM fuzzyness of dendritic dynamics (wave forms, continuum of feeds from senses and feedback loops).

  If we zoom up the hierarchy we witness the SAME dynamics but now at the scale of left and right hemispheres of the brain (with the equivalent of the soma in the form of the CC and so a mediation emphasis). Further considerations show the same dynamics across lobes within hemispheres and front/back areas within lobes – this is fractal stuff.

  When we then consider the PRODUCTS of our brains, especially in the form of categorisation systems, we find isomophism between the qualities of the categories and the qualities derivable from simple self-referencing of FM/AM aka differentiate/integrate aka anti-symmetric/symmetric; there is mediation present in the form of the asymmetric.

  SO - the focus is on identifying the fine details of these sorts of patterns since they are invarient across all scales of the neurology and ‘leak out’ into the structure of personalities, of collectives, and the literature and language tools of such.

  IOW we do KNOW, even if vaguely, what is going on in that we can trace inputs to outputs and mediation dynamics inbetween – and that from simple mechanical operations to complex thought processes (as I cover in the structures of our metaphors where such are often taken literally).

  I think the issues with a lot of neuroscience work is that it has got to the level of analysis of the leaves on the trees in the forest. My point is that there is a plethora of material going back 100 years that allows us to step back and view the forest with better developed vision. In doing so we find the patterns I have identified; the hierarchy, and the anti-symmetric/asymmetric/symmetric dynamics where the asymmetric is a source of self-referencing for the generation of languages to communicate the anti-symmmetric/symmetric dynamics overall of a perpetual modification of the baseline for dealing with, adapting to, reality. This process, overall and covering the long term, is about energy conservation and so the ‘need’ for habituation that allows context to PUSH a life form.

  IOW to get a general picture of what is going on at the micro levels, focus on what is being produced or more so what is SAME in those productions since THAT gives us a clue as to the nature of the neurology and what it is doing.

  The feedback is in our models being derived from our brains and so reflective of those brains. Wherever we look we will see the identified patterns – LOCAL contexts will customise, relabel, differ in forms of manifestation etc, but overall we are dealing with part/wholes, anti-symmetric/symmetric. These forms do double duty in that they are also interpretable from a relational focus on static relationships and dynamic relationships within levels of hierarchies and across levels.

  Chris.
  http://members.iimetro.com.au/~lofting/myweb/introIDM.html

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