In the process of moving from a whole to its parts, a process of zooming-in for details, so we move from a general
to the increasingly particular as we extract features from the 'background' into the 'foreground' (see refs on
figures from ground processing in the brain)
As we flesh-out particulars so we gain a better understanding of the whole through the feedback, where the extraction
and clear identification (labels etc) of a particular allows us to put that particular back into the whole but
now clearly, crisply, identified and so no longer 'vague'. That clarity can then contribute to identifying associated
particulars in immediate proximity to the one analysed.
From the level of the neurology, ANY movement from general to particular is a movement from low frequency processing
(more so Amplitude Modulation (AM) in input areas (dendrites) to high frequency processing (more so Frequency Modulation
(FM) in output areas (axon)), where it is the requirement of high frequency that allows for fine differentiation,
finer resolution power, of parts/aspects. (this allows for a more LOCAL but very CLEAR (FM quality), single context
(XOR) perspective associated more with left hemisphere or general differentiating areas of the brain as compared
to the more general, vague (AM quality), multiple context perspectives (AND) associated with the right hemisphere
or general integrating areas of the brain. - see an extract covering this perspective -
and refer to the figure below.
In the material referenced in the above extract, we find the single context serves as a base frequency from which
to interpret information - this reflects a 'holographic' nature where we need the encoding frequency or lower
to recall information and this is generalised into the notions of 'state-specific' memories. Under extremely high
energy-utilising events, and so very high frequencies, we have 'flash-bulb' memories where these memories are more
'universal' and so context-free for recall (e.g. "where were you on Sept 11th, 2001?" )
The left/right asymmetry shows the 'base' frequency present in the left hemisphere as also being present in the
right hemisphere but with no exaggeration - in other words the right shows more a pool of POTENTIALS, all frequencies
of 'equal' nature, and the left shows an ACTUALISATION of one of those, an exaggeration, to serve as the 'ground'
for interpretation.
That said, the left/right distinctions reflect the asymmetric dynamic at the level of the cortex but this is 'fractal-like'
in that as we zoom-in for details so we find the same distinctions WITHIN each hemisphere etc etc (e.g. relationship
of left temporal lobe to left parietal lobe, zoom-in again and the relationship is front left temporal to back
etc etc) As well as across each hemisphere from back (more general) to front (more differentiating, with integrating
more 'sequence' oriented).
We could overlay each of these general-to-particular patterns with an abstraction of the neuron - the core fractal
'shape' at work.
We can represent this movement from general to particular, and so the increase in precision in identification,
by representing each level of 'meaning' in the form of a particular frequency - and we can use the recursion of
a dichotomy to show this process where each level of recursion is represented by increasing the frequency by a
power of 2.
Note that to implement XOR in the brain requires two neurons, one feeding-back on the other, and so a form of self-referencing.
The natural oscillations in the brain span specialist areas of differentiating/integrating such that, given the
attention system and its ability to focus, allows for 'passive' recursion in a bounded space of the XOR/AND dynamic.
The set of POSSIBLE combinations of XOR/AND derived from the recursion can be used as a toolkit of 'meanings'…..
Given six 'loops' of recursion of a dichotomy, we move from a position of identifying each element of the dichotomy
as a wave cycle to give us a base waveform with a frequency of two cycles per second. The "WHOLE" as
such is a waveform of one cycle per second and the dichotomy reflects the first level of differentiating, and so
a whole is 'cut' into two, vague, but distinct, parts such as 'positive' / 'negative' or 'on' / 'off' etc.
Thus, using the differentiating/left vs the integrating/right, out of the right, the side associated by Gazzaniga
with "AS IS", comes our zooming-in for details analysis and so the particular that gives us "AS
INTERPRETED" - it is this position more associated with mediation dynamics and the nature of consciousness
as compared to instincts/habits that are properties of our as-is nature as species-members)
As we recurse the dichotomy so we create finer distinctions made-up of summing the different frequencies of each
level of recursion. Thus, for example, at the sixth level we have 26 = 64 representations of 'parts'
of the whole, or more so exaggerations of aspects of the whole where the whole is of all aspects encoded as POTENTIALS
and LOCAL CONTEXT will then favour the eliciting of one aspect in response to that context over all of the others.
(see below comments on emotions on the surface of the face)
We can represent these aspects using the discrete terms of bit values, 0/1, as long as we recognise that each bit
in a representation made-up of a string of bits is associated with a particular frequency based on the position
of the bit as a power of 2. Thus in the representation in a bit sequence form of 110111, the first bit represents
a frequency of 2 cycles per second (cps), the second of 4cps, the third of 8cps (but here it is 'off' or 'negative'
and so there is no activity or a cancelling activity), the fourth of 16cps, the fifth of 32cps, and the sixth of
64cps. The SUM of these frequencies (and so reflecting a superposition) will give a unique pattern, a wave form,
representing a particular quality - '110111'. (Note if we use the binary representation of a wave, then we are
dealing with summing 'square' waves - the analogue version being the 'normal' sine wave)
Since increase in frequency is associated with increase in differentiation and so in precision of expression, so
the representation of 000000 is a representation of a POTENTIAL, or vague, and the representation of 111111 is
a representation of full, total, ACTUALISATION, or crisp.
At the sixth level of recursion we have 64 '6-bit' forms, representations. Since the neurology appears to work
in a more binary format (0s/1s plus modulation/mediation) so these bit representations (and those derived from
further recursion where we add no more other than making finer distinctions) can represent DIFFERENCES in expression
of neurological states that in turn reflect DIFFERENCES in expression of general physiological states of any neuron-dependent
life forms - and as such are representations of states derived from interaction of life form with local context.
The bit representations reflect the ever-improving differentiation of particulars from the general that is represented
in the first bit. As we add bits so we create new 'generals', new 'contexts' within which the next set of bits
function. For example, in the representation of 1111, this sets a context, a general, for the next PAIR of representations
of 11111 and 11110, and so text, particulars that in turn each become context for further development.
What the discrete nature of bit representations 'hide' is the fact that these representations are all WITHIN the
whole and as such are expressions of the whole as POTENTIALS - context can push the whole's "buttons"
to elicit a particular expression, the 'bestfit', out of the set of possible expressions, but those expressions
not explicitly expressed form into a sequence of expressions sorted from 'bestfit-1' to 'worstfit'; in other words
they contribute to the expression.
The above dynamic reflects a topological perspective where a bounded surface is pulled this way and that and in
that pulling so one area influences, or draws into its expression, all of the other areas (note how this allows
for TWO forms of identification - the explicit and the implicit - the latter where analysis of behaviour of other
areas can lead to implying a particular area's behaviour.
This 'rubber sheet, geometric' perspective being the case, why use 'bit' representations where they can 'distort'
one's perspective of this perspective? Surely the fact is that rather than dealing with discrete units we are more
so dealing with a sea upon which are expressed local conditions in the form of wave dynamics etc.?
The benefits of bit representations is this: since each representation is the expression of an ASPECT of the WHOLE
so in that expression will be ALL of the WHOLE and so all of the other aspects will contribute in defining the
expressed aspect.
In other words, each "ASPECT" is a presentation of the whole in some form of locally-determined expression;
the analogy is to facial expressions where the whole is the face and each complement of muscles etc, when acted-upon,
bring out a particular expression. We see this expressed on the face in the form of emotional expressions (with
the set of POSSIBLE expressions derived from recursing the fight/flight
dichotomy at the core brain areas (amygdala) and on into a general
cortex dynamics of emotion) and so see a template for communications (the face playing a major part in non-verbal
communications and so allowing for the generalisation of facial expressions into general expressions. We can generalise
this to cover the sensory cortex of the brain as the bounded surface and dynamics across that surface elicit local
expressions etc - same principles, different scales. This allows for such events as synesthesia
where specialist senses data is 'confused'. All of this moves us into the realm of "regular" vs "small
world" networks where LOCAL context, and that includes sensory biases, can 'customise' the set of POSSIBLE,
universal, expressions (regular network) into a set of refined LOCAL expressions (a small world network where these
local expressions in turn can be considered as 'universals' from that local level))
How can we extract from each particular expression the contributions of all of the others towards that particular
expression? The use of bits reflects the use of high energy analysis, of differentiating, of high frequency processing.
Neurologically this is the realm of XOR, the EXCLUSIVE OR, where this realm allows for high precision differentiation
of parts from a whole (and that includes attempts to extract what appear to be parts but are not - as we find in
sensory paradox processing )
In the analysis of the brain overall, so we keep coming across the XOR/AND dynamic where the AND manages all that
is 'linked together' and so a relational bias, and the XOR manages discrete units and so an objects bias (But WITHIN
each object we find integration, AND-ness, in the form of rigid hierarchy etc).
As mentioned before, we can in fact trace this XOR-AND dynamic down to the level of the neuron (below figure),
where the AND nature is represented in the dendrite regions (AM bias, wave) and the XOR nature in the axon regions
(FM bias, pulse) - with the basic dynamic that of a analogue-to-digital converter as we extract details from a
whole (and feedback allows for refinement of that whole such that we can extract particulars, refine them, and
re-insert them into the 'whole' to give a more refined response to some stimulus; we can refine instincts/habits
and/or create new ones that allow us as species-members to interact organically, immediately, holistically, with
the context).
The XOR/AND dichotomy reflects the characteristics of an asymmetric dichotomy where the discrete, the XOR, results
from the zooming-in, the exaggeration, of a particular in the realm of AND. This form of dichotomy, when recursed,
will give us a spectrum, showing its association with power laws etc. In this spectrum, using analogy to light,
so the high energy 'end' is associated with bit representations of 111111 (blue/ultra-violet) as is the low energy
'end' associated with bit representations of 000000 (red/infra-red). In other words the AND end is an end of POTENTIALS
or 'vague' relationships when compared to the XOR end is an end of ACTUALS (and so of crisp "thing-ness"
etc - note that the recursion will in fact create a dimension made-up of PAIRS of object/relationship categories
getting increasingly more 'discrete' in categorisation as we move towards the high energy end of the dimension)
When working in the realm of XOR and AND we are working in the realm of 'logic operators'. In this realm we find
that to extract the descriptions of the contributions of all possible expressions to any particular expression
we XOR all of the other expressions in their bit forms with the bit form of the particular expression. What we
are doing is what the brain appears to do in extracting details from a complex system, it applies XOR to the AND
realm (and this can cause paradox at times where we try to reduce the irreducible).
How does this work? Each bit in the bit-representations represents a particular frequency that is contributing
to an expression. By turning OFF all other frequencies BAR the particular frequency or frequencies we wish to analyse
we set-up a 'bit mask' that, when XOR-ed with any particular expression will bring out that bit-mask's expression
THROUGH the particular expression. For example, if we have a bit pattern of 100001, then XOR-ing that pattern with,
for example, 101110 will give us:
100001
101110
(The XOR 'rules' are, given a column of two bits, the result is 1 if the bits in the column are ordered 01 or 10, any other ordering (00 or 11) gives a result of 0)
This derived pattern is an analogy in that it describes by analogy the expression of 100001 THROUGH 101110. This
dynamic is a property of the recursion and it allows us to deriving meaning of some particular through reference
to all of the other particulars contributing to the whole.
What we are dealing with here is the basic dynamics of a finite language where that language is here in the form
of 'qualities' expressed as summing frequencies. Since each level of recursion will create a FINITE set of qualities,
so their use in representing and so communicating 'all there is', is through ANALOGY/METAPHOR in that we cannot
have a 1:1 mapping of our finite qualities to 'all there is' at the level of particulars, but we can have it at
the level of analogies/generals. (in formal language we move into the realm of the noun/verb dichotomy that when
recursed gives us the full set of noun/verb forms that we then localise through labels that tie the universals
to a local context)
Thus, our expression of the '100001-ness' of 101110 can only be achieved through reference to some other bit-representation
in the set of possible bit-representations - and here it is 001111. In other words the "100001-ness of 101110
is LIKE the (under-played) characteristics represented by 001111" (this is clearly demonstrated in analysis
of the generation of some of our basic, specialist, typologies, as discussed
elsewhere)
The question now is "What are these mentioned 'characteristics'"? We have as yet not touched on the details
of what these bit values represent OTHER than "frequencies" - but we have made mention of recursion of
the dichotomy of fight/flight, where that recursion gives us the spectrum of basic emotions. That recursion can
be REPRESENTED using the bit patterns such that (a) ANY dichotomy can be recursed and represented using the described
bit patterns, and (b) EACH quality derived can be described through reference to all of the other qualities derived
using the described XOR dynamic. What we are dealing with here is isomorphism - same qualities, different labels
(see, for example, the translation page
)
This is all possible since what we are describing is the root of meaning and its expression. That root is in the
dynamics of the neurology where that dynamic elicits patterns of meaning from 'mindless' acts of differentiating/integrating
data. The recursion of the differentiate/integrate dichotomy (something guaranteed by the brain's natural oscillation
across brain areas focused on differentiating or integrating) will elicit patterns representable using bit patterns
and they apply to ANY synonym of the differentiate/integrate dichotomy - the most common in the neurology being
the dichotomy of the GENERAL qualities of WHAT/WHERE (particularised into the sets of (what, who, which) and (when,
where, how))
Closer examination shows us that we are in fact dealing with TWO forms of dichotomy, one symmetric and more LOCAL,
one asymmetric and more GLOBAL. The symmetric dichotomy associates with data reflected in Gaussian, or Normal,
Distributions - a focus on a shared context (and so sameness) out of which we wish to extract difference. On the
other hand, the asymmetric dichotomy associates with data reflected in distributions associated with spectrums/power
laws and so different contexts across which we can identify sameness. (and so the 'high frequency' element is derived
from the 'low frequency' element, XOR from AND, crisp from vague etc etc)
As demonstrated elsewhere (see wave
interpretations for a particular mapping of waves to meaning in a specialist context; also see wave
structure showing isomorphism across specialist interpretations) , we can, given just six levels of recursion,
generate a set of qualities that become universals in their use to communicating meaning. LOCAL context allows
for the linking of these universals with that context through derivation of labels, such that that relationship
can elicit a specialist language that aims to hide the sameness of the universals across different contexts by
the use of labels to emphasise difference. In this hiding, so the local customisation can skew the interpretations
of the universals, and even limit their full expression, and so create a 'small world' network out of the set of
universals working as a 'regular' or 'context-free' network.
Each 'small world' is a specialisation that from WITHIN can appear to be the world 'as is' rather than 'as interpreted'. Thus we can take the 'figure' for the 'ground' where there is an increase in hierarchic perspectives the details we go for - we move from a semantics perspective to an ever increasing syntax perspective where all that matters is one's 'correct' position in the hierarchy.
(1)
Neuron. 2005 Jul 7;47(1):155-66.
Figure and ground in the visual cortex: v2 combines stereoscopic cues with gestalt rules.
Qiu FT, von der Heydt R.
Department of Neuroscience, Johns Hopkins University 3400 North Charles Street, Baltimore, MD 21218, USA.
Figure-ground organization is a process by which the visual system identifies some image regions as foreground
and others as background, inferring 3D layout from 2D displays. A recent study reported that edge responses of
neurons in area V2 are selective for side-of-figure, suggesting that figure-ground organization is encoded in the
contour signals (border ownership coding). Here, we show that area V2 combines two strategies of computation, one
that exploits binocular stereoscopic information for the definition of local depth order, and another that exploits
the global configuration of contours (Gestalt factors). These are combined in single neurons so that the "near"
side of the preferred 3D edge generally coincides with the preferred side-of-figure in 2D displays. Thus, area
V2 represents the borders of 2D figures as edges of surfaces, as if the figures were objects in 3D space. Even
in 3D displays, Gestalt factors influence the responses and can enhance or null the stereoscopic depth information.
Related commentary to the above:
How the brain understands pictures
The figure is famous: a deceptively simple line drawing that at first glance resembles a vase and, at the next,
a pair of human faces in profile. When you look at this figure, your brain must rapidly decide what the various
lines denote. Are they the outlines of the vase or the borders of two faces? How does your brain decide?
It does so in a fraction of a second via special nerve circuits in the brain's visual center that automatically
organize information into a "whole" even as an individual's gaze and attention are focused on only one
part, according to Johns Hopkins researchers writing in a recent issue of the journal Neuron.
"Our paper answers the century-old question of the basis of subconscious processes in visual perception, specifically,
the phenomenon of figure-ground organization," said Rudiger von der Heydt, a professor in the Zanvyl Krieger
Mind-Brain Institute. "Early in the 20th century, the Gestalt psychologists postulated the existence of mechanisms
that process visual information automatically and independently of what we know, think or expect. Since then, there
has always been the question as to whether these mechanisms actually exist. They do. Our work suggests that the
system continuously organizes the whole scene, even though we usually are attending only to a small part of it."
The report, based on recordings of nerve cells in the visual cortex of macaque monkeys, suggests that this automatic
processing of images is repeated each time an individual looks at something new, usually three to four times per
second. What's more, the brain provides what von der Heydt calls "a sophisticated program" to select
and process the information that is relevant at any given moment.
"The result of this organization is an internal data structure, quite similar to a database, that allows the
attention mechanism to work efficiently," von der Heydt said. "An image can be compared with a bag of
thousands of little Lego blocks in chaotic order. To pay attention to an object in space, the visual system first
has to arrange this bag of blocks into useful 'chunks' and provide threads by which one or the other chunk can
be pulled out for further processing."
He noted that the research provides the theoretical foundation that might one day lead to better diagnosis and
treatment of human brain disorders.
"The last decades have seen rapid progress in the neurosciences at a very broad front, particularly at the
molecular and cellular levels, and this progress makes it increasingly clear that we still lack sufficient understanding
of brain function at the 'system level,'" he said. "We need to understand the basis of mental processes.
Single cell recording in animals is only one approach to this formidable task. It is complemented by new brain
imaging techniques, traditional psychophysics, psychology and computational and theoretical neuroscience. … Understanding
the function of the visual cortex will help to interpret neurological symptoms in diseases that produce disorders
of vision."
###
This work was funded by grants from the National Institutes of Health.
The paper, "Figure and Ground in Visual Cortex: V2 Combines Stereoscopic Cues with Gestalt Rules" appeared
in the July 7, 2005, issue of Neuron (Volume 47).
(2)
Neuroreport. 2005 Sep 8;16(13):1483-1487
Figure-ground segregation requires two distinct periods of activity in V1: a transcranial magnetic stimulation
study.
Heinen K, Jolij J, Lamme VA.
1Anatomy Department, Wellcome Department of Imaging Neuroscience, University College London, Gower Street, London
WC1E6BT, UK 2Cognitive Neuroscience Group, Department of Psychology, The Netherlands Ophthalmic Research Institute,
University of Amsterdam, Amsterdam, The Netherlands.
Discriminating objects from their surroundings by the visual system is known as figure-ground segregation. This
process entails two different subprocesses: boundary detection and subsequent surface segregation or 'filling in'.
In this study, we used transcranial magnetic stimulation to test the hypothesis that temporally distinct processes
in V1 and related early visual areas such as V2 or V3 are causally related to the process of figure-ground segregation.
Our results indicate that correct discrimination between two visual stimuli, which relies on figure-ground segregation,
requires two separate periods of information processing in the early visual cortex: one around 130-160 ms and the
other around 250-280 ms.
(3)
Psychol Med. 2005 Jul;35(7):1043-51. Related Articles, Links
Lateral interactions in the visual cortex of patients with schizophrenia and bipolar disorder.
Keri S, Kelemen O, Benedek G, Janka Z.
Department of Psychiatry, University of Szeged, Szeged, Hungary. szkeri@phys.szote.u-szeged.hu
BACKGROUND: Schizophrenia is associated with perceptual organization deficits and abnormal neuronal connectivity
has been described in early visual areas. The purpose of this study was to investigate the functional integrity
of lateral connections in early visual areas of patients with schizophrenia and type I bipolar disorder with a
history of psychosis. METHOD: Twenty-four out-patients with schizophrenia, 22 out-patients with bipolar disorder,
and 20 healthy control subjects participated in the study. Using a computer-assisted psychophysical test, contrast
thresholds were measured for centrally presented target stimuli (Gabor patches), which were surrounded by two collinear
flankers. Target-to-flanker distances were 0, 1, 2, 3, 4, 6, 9 and 122. Psychophysical measures were contrast threshold
changes at each target-to-flanker distance compared with baseline thresholds determined for isolated targets with
no flankers. Clinical measures included IQ, positive, negative, and depressive symptoms. Results. In patients with
schizophrenia, flankers did not facilitate contrast detection for target stimuli at 2-6 lambda distances compared
to controls [effect size (Cohen's d): 1.25-1.42]. The inhibitory effect of flankers (0 and 1lambda) and contrast
thresholds in the absence of flankers were spared. Patients with bipolar disorder did not differ from the controls.
Medicated and non-medicated patients displayed similar performances. Positive and negative symptoms and depression
did not correlate with contrast threshold values. CONCLUSIONS: Excitatory lateral connections in early visual cortex
are specifically impaired in patients with schizophrenia, which may contribute to perceptual disorders such as
unclear seeing, partial or skewed sight, disrupted rectilinearity, and abnormal figure-ground segregation.
(NOTE IN THE ABOVE THAT "abnormal figure-ground segregation" can be a source of 'creative' perspectives)
(4)
Neuron. 2005 Jul 7;47(1):5-8.
Resolving border disputes in midlevel vision.
Nakayama K.
Department of Psychology, Harvard University, Cambridge, MA 02138, USA
Two papers in this issue of Neuron specify the coding of border ownership, the basis of figure-ground segmentation,
in early extrastriate visual cortex (area V2). Recording from a population of neurons, Qiu and von der Heydt show
that border ownership assignments based on 2D images show the same bias when tested with stereopsis. Zhaoping shows
that a neural model of V2 can make appropriate border assignments based on 2D images.
(5)
Cereb Cortex. 2005 Apr 20;
Synchrony dynamics in monkey V1 predict success in visual detection.
van der Togt C, Kalitzin S, Spekreijse H, Lamme VA, Super H.
Vision and Cognition II, The Netherlands Ophthalmic Research Institute, Meibergdreef 47, 1105BA Amsterdam, The
Netherlands.
Behavioral measures such as expectancy and attention have been associated with the strength of synchronous neural
activity. On this basis, it is hypothesized that synchronous activity affects our ability to detect and recognize
visual objects. To investigate the role of synchronous activity in visual perception, we studied the magnitude
and precision of correlated activity, before and after stimulus presentation within the visual cortex (V1), in
relation to a monkey's performance in a figure-ground discrimination task. We show that during the period of stimulus
presentation a transition in synchronized activity occurs that is characterized by a reduction of the correlation
peak height and width. Before stimulus onset, broad peak correlations are observed that change towards thin peak
correlations after stimulus onset, due to a specific decrease of low-frequency components. The magnitude of the
transition in correlated activity is larger, i.e. a stronger desynchronization occurs, when the animal perceives
the stimulus correctly than when the animal fails to detect the stimulus. These results therefore show that a transition
in synchronous firing is important for the detection of sensory stimuli. We hypothesize that the transition in
synchrony reflects a change from loose and global neuronal interactions towards a finer temporal and spatial scale
of neuronal interactions, and that such a change in neuronal interactions is required for figure-ground discrimination.
Part A
(1) The hemispheres of the neocortex function as high and low band information filters.
The left hemisphere (in most, there is a BIAS here as well as genetic diversity that allows for differences in
the sameness) amplifies and process high frequency data. The right hemisphere processes low frequency data.
These processing biases are in spatial (visual) processing as well as auditory processing. Since these are the
dominant ways in which we process information they are strongly emphasised.
(A good reference is: Ivry, R.B., & Robertson, L.C.,(1998) "The Two Sides of Perception"
MITP It is mostly vision data with particular research by the authors as well as extensive reviews of other research
in this area.Audition is limited to two chapters).
Further data covering the whole visual system is in: Hoffman, D.D., (1998) "Visual Intelligence: How
we create what we see" Norton
For additional refs to cover the audition bias see: In general: McAdams, S., and Bigand, E., (Eds) (1993) "Thinking
in Sound" OUP, and In particular: Levarie, S., (1980) "Music as a Structural Model"
p236-239 IN Journal of Social Biol. Structure. 3)
The High/Low frequency processing has some interesting consequences namely:
(1.a) High frequency means 'wide' bandwidth (intensity) means clarity and so precision.
(1.b) High frequency means short range and so an emphasis on the local, the particular, and so a SINGLE context.
(1.c) Low frequency means narrow bandwidth means blurring and so approximations.
(1.d) Low frequency means long range and so an emphasis on the non-local, the general.
1.a + 1.b analogous to narrow spotlight, high beam. Intensity. Manic.
1.c + 1.d analogous to wide spotlight, 'diffuse' beam. Ambiant. Phobic.
(1.e) The right's bias to low frequencies means that detected general patterns will contain a larger range of frequencies
and so a link to multi-contexts whereas a particular frequency manifests a single context (see 1.b above). This
favours the left being 'tonic' or 'key' oriented and the right being more into harmonics and 'linkage' (harmonicA+harmonicB+harmonicC
etc).
(1.f) Although for any data the fundamental harmonic is processable by BOTH hemispheres, it is STRONGLY identified
in the left hemisphere. In the right hemisphere it is barely differentiated from the other harmonics; it is 'diffuse'
due to the low-frequence emphasis of the right.
(1.g) The left/right distinctions are repeated at lower scales, for example at the lobe level the same relationship
of particular-to-general is present in the relationship of temporal lobe to parietal lobe in BOTH hemispheres.
(The boundary is flexible, there is more of continuum from parietal to temporal and so no strong EITHER/OR line
in determining particular-general but the biases becomes 'obvious' reasonably quickly).
(1.h)The left/right distinctions are also at the neural columns levels within a lobe. E.g.
(A) the differentiation of left/right visual FIELDS in the occipital lobes is split into the interdigitations of left-eye data/right-eye data.
(B) the frontal lobes, in those areas linked to planning and pre-expression formatting, manifest the same pattern of interdigitations but at an abstract level with the interdigitation links being left hemisphere/right hemisphere. (see P. Goldman-Rakic's work in these areas. The original paper being:
- Goldman-Rakic, P.S., (1984) "Modular organization of the prefrontal cortex" IN Trends in Neurosciences Nove 1984 pp 419-424
(C) The primary auditory cortex reflects interdigitations to process audition-sourced wavelength/frequency data.
When you apply various dyes across the brain you see a pattern emerge that is like a fingerprint or the patterns
you see in nature on zebras etc etc What seems to be happening is that nature 'completes' the general individual
(bias to SAMENESS) and nurture (especially in infancy) act to particularise and so create the particular individual
(DIFFERENCE).
What is noteworthy is that the dye process brings out a hierarchic developing of the neocortex where scrapping
away the surface of the neocortex shows a diffusion of the dye, unless you change scale. (see for example:
What this hierarchic format suggests is that the left-high/right-low distinctions are possibly applicable not only
at the 'top'/'bottom' of the neocortex but also along the posterior-to-anterior of the whole brain, i.e. from the
'reptilian' brain upwards.
This arguement is reinforced by the tie of the basal ganglia to a sensitivity to CONTEXT, feedback processing and
so LOW frequency, harmonics, data. The basal ganglia is just 'underneath' the six layers of the neocortex. These
distinctions gives us at least a 3D format. (note that across the neocortex there are two 'paths', dorasal via
the occipatal-through-pariatal lobes, and ventral via the occipital-through-temporal lobes. The dorsal is more
sensitive to 'WHERE', the ventral to 'WHAT'.)
A good analogy for these left-high/right-low distinctions is the consideration of a gene encoded in DNA vs the
same gene encoded in mRNA. DNA coding manifests 'right hemisphere' processing where the gene is 'diffuse' in that
it is spread-out through the DNA strand(s). The process leading to expression involves the cut'n'paste of different
elements of the gene (i.e. summing of harmonics) into a single thread expressed in the form of a mRNA strand prior
to ribosome processing.
Thus the DNA format manifests approximations and the mRNA format manifests precision. The benefit of this, storing
the information in a split-up form, is that it allows for an ease in 'playing' with harmonics; e.g. viruses etc
were we see sections of strand that are thousands of years old and others that change 'hourly'. (I recall that
Bacterial DNA contains genes in a contiguous space which is too rigid, too all-or-nothing. Our format is more flexible.)
.....
With the above 'simple' left/right distinctions we then consider the next set of information:
(2) The sensory systems, although having unique areas for processing 'primary' data in the neocortex, SHARE neural
networks both BEFORE birth and in association areas in developing into adulthood.
This sharing implies the presence of hybridisation in expressions, by this the frequency data from DIFFERENT senses
can be combined to give an abstract ('virtual') waveform which captures the 'essence' of both senses and so a sense
of 'meaning' that is 'outside' of either sense.
The differentiation at the PRIMARY level is strong such that the degrees of synesthesia we find in infants soon
dissapears. How about secondary/tertiary areas? see below re emotions.
(Good ref: Stein, B.E., and Meredith, M.A., (1993) "The Merging of the Senses" MITP. There are a number
of popular texts as well on synesthesia etc)
What is implied by the sharing is the use of complex, sensory-based dichotomisations in the form of vision-data/audition-data
that are processed (a) in opposition (what I see is not what I hear) as well as (b) cooperation (what I see validates
what I hear - congruency). I will 'refine' the dichotomisation concepts further on.
(3) The process of habituation at the sensory (and associations) level suggests a system that has evolved to sense
DIFFERENCE and that once the difference has been categorised and experienced further to the degree of being 'common'
it enters the realm of SAMENESS and is then ignored; we do not have to keep identifying the 'old', just the 'new'
or variations on the 'old'.
(I recall this is covered to some degree in: Posner,M.I., Raichle, M.E., (1994) "Images of Mind"
Scientific American Library )
This emphasis on DIFFERENCE suggests the presence of genetically-determined 'seeds' in the form of fundamental
distinctions to 'something'. (1) above suggests SAMENESS in the form of an archetypal fundamental together with
a set of archetypal harmonics.
Samness links to the concept of a local, a particular. The work discussed in (1) shows that locals do not explicitly
influence/interfere with a non-local, generals, but non-locals can influence/interfere with locals. What this suggests
is that a sameness can be 'modified' by a difference. What is of interest here is that at the *implicit* level,
local distinctions can create general patterns but there is no 'intent'. E.g. the flocking of birds, neural network
synchronisations etc; interactions of 'SAMES' lead to an expression, a DIFFERENCE that is not sourcable to any
particular; the flock behavour continues even if a few of the flock wander off.(This data comes from complexity/chaos
research and in particular simulators used in Artifical Life programs).
(4) The hemispheres of the neocortex manifest a fundamental dichotomy in the form of a 1:many distinction.
There is a LOT of references possible here, enough to make it an axiom. We can just stick 'local' and just use
the data from (1) above, single, fundmental, harmonic to the left and multi frequences and so multi contexts to
the right.
The 1:many format ties to the processing (extraction/fitting) of TEXT from/into CONTEXT. This has been demonstrated
in rCBF studies on negation. In particular, the making of a request, where one wishes to satisfy a context (as
in asking a parent/spouse etc "can I go to X's place for dinner") puts the individual in a 'single context'
frame of mind. Approval of the request just satisfies the context and so a 'thank you' or 'great' and end of story.
But a refusal actually elicits a change in 'dominance' where there is a switch from 'left' to 'right'. What is
going on?
The original studies just noted an emotional bias to positive/neutral thinking to the left and negative and so
critical thinking to the right.
(See Gainotti, G., and Caltagirone, C., (eds) (1989) "Emotions and the Dual Brain" Springer-Verlag
for papers on processing negation etc)
However I find this general interpretation 'weak'. I would suggest that the switch more manifests the use of abductive
processes where in one form of abduction the individual switches to trying to find a context that can be introduced
to change the refusal to an approval (e.g. "But last time it was OK" or the initial "But why not?")
IOW you go through harmonics to find one that can be accentuated to get what you want.
This methodology, abduction, is common in us as a species where we hold a LOCAL text constant (the 1) and scan
through *different* contexts (the many) to get a match. (the difference of abduction from induction is that abduction
has, or assumes there is, a context that 'fits' the text. Induction starts local with no initial assumptions of
there being a contextual, general, link. For example, mathematical induction stays 'local' by simply emphasising
'if N is the case, consider N + 1.." This emphasises a more 'within' perspective, there is no need to step
outside of the local box other than perhaps 'a little'.)
(5) Emotion is the general response system to all sensory inputs, internally derived or externally derived.
As (4) has shown there seems to be an emotional 'tie' to left and right hemispheres. This has been supported over
more recent times through the work of such people as A. Demasio and J. Ledoux. In (4) there is also some work by
Doty, R.W., (1989) "Some anatomical substrates of emotion, and their bihemispheric coordination"
IN "Emotions and the Dual Brain" p57-82 (see
additional, more recent references)
This work links to the limbic system etc and leads to the realisation that it is sensory harmonics, colour from
vision and multi-frequencies (chords) from music that elicit 'refined' emotions and these harmonics are of course
in the form of frequencies. These 'refined' emotions, being 'many' linked tie to right hemisphere processing biases
and there is ample evidence to show that musical chords, colours etc, being SECONDARY+ and not fundamentals (black/white)
elicit a more right hemisphere response.
It is only with musical training do you get a more 'left' oriented response to music, especially when reading since
the 'dots' are very 'fundamental' in interpretations!; the dots are like words.
Combined with the information from (1) and (4) we can see how the left side is more often linked to 'single context'
expressions of emotion whereas the right is more 'multi-context'; there seems to be a degree of 'finess' linked
to the right since the expressions of emotions other than as pure forms (all hate, all love, single colour (?),
single note etc) require multi-frequency data; the entanglement of harmonics to give more subtle expressions and
this is low, multi-frequency data, something the right does 'better' with than the left.(Perhaps we need to make
the distinctions of emotions (raw) from feelings (refined) but then this 'containment' of expression is not 'precise',
it needs decoding, interpretation. M. Gazzaniga links interpretation (extracting the one from the many) to the
left.).
There has been strong links in various texts to the right being 'better' at processing emotions/feelings and the
data from the other references above suggest that, other than extreme expressions of emotions, there is more of
a bias to emotions being 'in the background' to a communications and so more 'low' in format and so more favouring
of the right hemisphere. As we saw from (4) this includes the concept of negation where negation is 'NOT' left,
it is considered a harmonic in that to express negation you need a fundamental first.
(See the reviews on hemispheres and emotion in such texts as: Springer, S.P., & Deutsch, G., (1998) "Left
Brain, Right Brain : Perspectives from Cognitive Neuroscience (5th Edition)" Freeman, or the ref in
(4) above, or any of Ledoux or Demasio books).
To summarise things so far I think we can say that:
The analysis and synthesis of information is done through a set of filters that act to distinguish 'precise' data
from 'approximations'; to make 'clear' identifications as well as allow for RE-identification.
This analysis/synthesis process lead to the use of set of fundamental filters expressed in the form of 1:many dichotomies:
DIFFERENCE : SAMENESS
PARTICULAR, LOCAL : GENERAL, NON-LOCAL
TEXT : CONTEXT
PRECISE : APPROXIMATE
POSITIVE/NEUTRAL : NEGATIVE-CRITICAL (dichotomies of emotion. These distinctions are already one level passed the
base dichotomy of positive/negative emotion. I will cover this later.)
I suggest that these are 'collapsable' into the dichotomy of
OBJECT : RELATIONSHIPS
and the locational dichotomy of
WITHIN/BEHIND : BETWEEN
Other sources (not needed but useful) verify the general form of these dichotomies with the neurology showing
a general bias to the WHAT/WHERE dichotomy, with the WHAT having within it the WHO and the WHICH
(categorical) and the WHERE having within it the HOW and the WHEN (coordinal).
The WHAT/WHERE dichotomy is itself collapsable into the root, general, dichotomy of
Differentiating/Integrating
At first you may think that these dichotomisations seem intuitively 'weak', too 'EITHER/OR', however in the above
link I show the results of applying dichotomies recursively such that the A/~A becomes a continuum and that becomes
the basis for determining meaning to a degree where all disciplines seem to serve as metaphors for the particular
describing of object/relationships data in a particular context. Those metaphors that are close to the 'real' have
a more associative emphasis (1:1) but are in fact metaphors in that the lexicons involved contain words that link
to the summing of sensory data and as such, these words 'transfer' or 'carry' the meanings.