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<div class="moz-cite-prefix">Dear Jose Luis and Ramon,<br>
<br>
Many thanks for the elegant text. The general view provided looks
plausible and as you say it seems to dovetail with other main
approaches to brain integration, perhaps a little bit more
realistic (some critics of Tononi's "phi" have argued that a
mobile phone's circuitry has a higher metric of integrated
information, thus conscious activity, that the conscious brain
itself). Anyhow, some of my concerns with the text below would
relate with:<br>
<br>
1. The entropy concept presented. It appears as a measurement
(log) of the possible configurations of the "connected" (relative
synchrony) networks. Given that it is obtained from EEG or MEG
recordings it displays an evident objectivity, but given all the
theoretical weight that later on incorporates, do you think it has
sufficient generativity or relevance to influence (to capture?)
the ongoing brain dynamics? The subsequent complexity metrics JLZC
would appear a little more potent or realistic on that regard. If
my interpretation is not too wrong, they would respectively mean
the possible combinatorics of info channels, and the actual flows
between them. For my taste, this seems to be a form of "neural
entropy" to clearly distinguish from physical entropy (indicated
for the non-physicists, like me, otherwise we easily incur into
trouble).<br>
<br>
2. Along that scheme, a working brain listening to its sensory
affordances would experiment then a moderate entropy/complexity
increase (isn't it?). Further if the inner processes ring some
alarm, that entropy would escalate enormously. But later
problem-solving mechanisms could efficiently decrease that
entropy, if successful. Would you agree that behavioral problem
solving could somehow be put in abstract terms of
entropy/complexity management? But subsequently establishing a
variational principle (Friston, Sengupta) could be tricky, for as
you point out, the brain does not blindly maximize: it
"optimizes."<br>
<br>
3. The subconscious. It appeared in the previous discussion
session (on narratives). Do you think the the brain rest
activation (default mode network) could be considered as a more
reliable referent when talking about the subconscious mechanisms
of creativity, feelings, etc? All the brain areas relatively
silent in the left side of your figure, when transiently connected
with some portion of the central cluster of the conscious space,
could not bring that stroke of creativity, geniality, etc.? <br>
<br>
I will appreciate your responses on these crude
reflections/comments.<br>
<br>
Best wishes and Happy New Year to all FISers!<br>
--Pedro<br>
<br>
<br>
<br>
<br>
El 04/01/2019 a las 14:40, jose luis perez velazquez escribió:<br>
</div>
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<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><b><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">Towards
a statistical mechanics of cognition: </span></b><b><span
style="font-size:12pt;font-family:"Times New
Roman",serif">Consciousness as a global property of
brain dynamic
activity </span></b></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif">As a new year’s lecture, we present our
recent work
that seeks general principles of the organization of the
cellular collective
activity in the brain associated with conscious awareness.
Our purpose is</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> to
identify features of brain organization that are optimal for
sensory
processing, and that may guide the emergence of cognition
and consciousness. We
follow the thermodynamic approach: find a state functional
which reflects the nature
of the states attained by the system and that is influenced
by some observables.
Considering what is known about how the nervous system
functions ―and that brain
activity is described from EEG, MEG or functional
neuroimaging as a
superposition of dynamics at different time scales― the
“nature of brain states”
consists of patterns of coordinated activity, that is,
correlations of cellular
(neuronal) activity normally measured as coherence or
synchrony, hence neural
synchronization is a fundamental observable and constitutes
an appropriate
metric to characterise nervous system dynamics.</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> We also follow the classic
approach in physics
when it comes to understanding collective behaviours of
systems composed of a
myriad of units: the assessment of the number of possible
configurations, or
microstates, that the system can adopt.
In our study we focus on the collective level of description
and assume
that coordinated patterns of brain activity evolve due to
interactions of
mesoscopic areas. Thus we use several types of brain
recordings (intracerebral
EEG, scalp EEG and MEG) reflecting the mesoscale level to
inspect not only
superficial cortical activity but also that of deeper
structures in conscious
and unconscious states, and calculate the number of
“connections” between these
areas and the associated entropy and complexity.</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif">The methods are detailed in Guevara Erra
et al. (2016)
and Mateos et al. (2017). Suffice to say that we compute a
phase synchrony
index from two brain signals (corresponding to two brain
areas) and declare the
areas “connected” if the index is higher than the average
synchrony obtained
from surrogates, and “disconnected” if the index is lower. </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> It must be noted that,
while normally
neuroscientists use the words synchrony and connectivity as
synonymous, in
reality phase synchrony analysis reveals only a correlation
between the phases
of the oscillations between two signals, and not a real
connectivity which
depends on several other factors</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif">; this is an
important topic but we have no space to discuss it here
(some of these
consideration are expounded in some chapters in ‘</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">The
Brain-Behaviour Continuum―The subtle transition between
sanity and insanity’ (</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif">Perez Velazquez and Frantseva, 2011).</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">Hence,
the number of “connected” brain networks is determined from
the recordings in
the distinct states: conscious (awake) and unconscious
(sleep −slow wave and
REM―, coma and epileptic seizures), and the whole collection
of connected and
not connected networks constitutes our macrostate of the
brain. </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif">An entropy value was then computed for
the number of possible
configurations of connected brain networks. </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">The entropy of
this macrostate is given by the logarithm of the number of
combinations.</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">We found a surprisingly
simple result:
normal wakeful states are characterised by the greatest
number of possible
configurations of interactions between brain networks,
representing highest
entropy values. Unconscious states have lower number of
configurations, that
is, lower entropy. Therefore, the information content is
larger in the network
associated to conscious states, suggesting that
consciousness could be the result
of an optimization of information processing. This result is
not too
surprising, for, as </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif">Shinbrot and Muzio (Nature 410:251-258,
2001) already
said, Nature chooses states that maximize the number of
particle rearrangements
(in our case it is the rearrangement of connected cell
networks).</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif">The following schematic figure summarises
the main
concept derived from the study.</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span></p>
<div><img src="cid:part1.2C128104.B5DF8E1F@aragon.es"
alt="image.png" class="" height="173" width="390"><br>
</div>
<br>
<p class="MsoNormal" style="margin:0cm 0.2pt 0.0001pt
0cm;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"> </span></p>
<p class="MsoNormal" style="margin:0cm 0.2pt 0.0001pt
0cm;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">The
figure </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"
lang="EN-GB">represents the proposed
general scheme of the relation between global brain
connectivity and
behavioural states. Normal alertness resides at the top of
the curve
representing the number of configurations of connections the
system can adopt,
or the associated entropy. The maximisation of the
configurations (microstates)
provides the variability in brain activity needed for normal
sensorimotor
action. Abnormal, or unconscious states like sleep, are
located farther from
the top, and are characterised by either large (e.g. in
epileptic seizures) or
small number of “connected” networks therefore exhibiting
lower number of
microstates (hence lower entropy) that are not optimal for
sensorimotor processing.</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">However,
the entropy thus computed, as explained in the two
aforementioned papers,
represents a global measure of the organization of brain
cell ensembles, hence,
at the macroscale level. Therefore, next we examined
activity at the lower
level, namely the variability in the connections between
brain networks; let’s
call this the “microscopic” level (although we are still
working with signals
that represent the macroscopic scale, do not get confused!).
</span><span style="font-size:12pt;font-family:"Times New
Roman",serif">Having found maximal entropy in conscious
states, the microscopic nature
of the configurations of connections was evaluated using an
adequate complexity
measure derived from the Lempel-Ziv complexity, the Joint
Lempel-Ziv Complexity
(JLZC). This method allows for the assessment of the
variability at short time
scales of the configurations of connected networks: the
establishment and
dissolution of “connections” (for details of this study,
please see Mateos et
al., 2017). Higher complexity was found in states
characterised not only by
conscious awareness but also by subconscious cognitive
processing, such as
during sleep stages, where it is known there is information
processing and not
only during REM episodes (dreaming) but also during slow
wave sleep (</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">Stickgold,
2001)</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif">. Thus, even in moments of global
unconsciousness
there can be substantial processing, which is revealed upon
a closer scrutiny
at the microscale level, as that provided by the JLZC. </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif">The results provide evidence for the
notion that
ongoing transformations of information in the brain are
reflected in the
variability and fluctuations in the functional connections
among brain cell
ensembles (large entropy of the number of possible
configurations and
concomitant large complexity in the variability of the
configurations of the
connections), which manifest in aspects of consciousness.
The crucial aspect
for a healthy brain dynamics then is not to reach maximum
number of units
(neurons or networks) interacting, but rather the largest
possible number of
configurations (allowed by the constraints). As such, the
result of high global
entropy at the macro level and concomitant high JLZC
supports the global nature
of conscious awareness, because even though there is high
JLZC in some unconscious
states, the macroscopic entropy is low in these states;
therefore, conscious
awareness needs high global entropy, whereas the high
complexity in some
unconscious states like sleep reflects information
processing but does not
reach “awareness”. On the other hand, we found that in
pathological unconscious
states like seizures or coma both the global entropy and the
JLZC are low. In
these pathological states, unlike during sleep, there is
almost no information
processing.</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif">The global
nature of consciousness is advocated by several theories of
cognition. In fact,
we think our</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">
findings encapsulate three main current theories of
cognition, as discussed in
the papers, namely, the Global Workspace Theory, the
Information Integrated Theory,
and the notion of metastability of brain states. It is well
known that neurophysiological
recordings of brain activity demonstrate fluctuating
patterns of cellular
interactions, variability that allows for a wide range of
states or
configurations of connections of distributed networks
exchanging information, that
support the flexibility needed to process sensory inputs and
execute motor
actions. Recent years have seen a surge in the study of
fluctuations in brain
coordinated activity, studies that have raised conceptual
frameworks such as
that of metastable dynamics and that have motivated interest
in the practical
application of assessments of nervous system variability for
clinical purposes.
Of course the prominent question is how to describe the
organising principles
of this cellular collective activity which allow features
associated with
consciousness to emerge. This is the objective of our work.</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">In
conclusion, and as </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif">an extension of previous work [Perez
Velazquez, 2009] where
it was proposed that a general organizing principle of
natural phenomena is the
tendency toward maximal —more probable— distribution of
energy, we venture that
the brain organization optimal for conscious awareness will
be a manifestation
of the tendency towards a widespread distribution of energy
(or, equivalently,
maximal information exchange). Whereas we do not directly
deal with energy or
information in our work, as we focus on the number of
(micro)states or
combinations of connected signals derived from specific
types of
neurophysiological recordings, the results obtained are
consistent with
conscious awareness being associated with widespread
distribution of
“information” among brain cell ensembles.</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">In
summary, these studies represent our preliminary attempt at
finding organising
principles of brain function that will help to guide in a
more formal sense
inquiry into how consciousness arises from the organization
of matter. The
extension of this work that we are now carrying out includes
a description of the
evolution equation of brain dynamics using a probabilistic
framework incorporating
the probabilities of connections among brain cell networks.
But this is a story
for a future talk! In the meantime,
buena suerte for the new year we just started… even though I
don’t really
believe in luck but this is another story too, one about
determinism and
stochasticity..</span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;text-indent:36pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><b><span
style="font-size:12pt;font-family:"Times New
Roman",serif;text-transform:uppercase">References</span></b></p>
<p class="MsoNormal"
style="text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif">R. Guevara Erra, D. M. Mateos, R.
Wennberg, J.L. Perez Velazquez (2016) </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">Statistical
mechanics of consciousness: Maximization of information
content of network is
associated with conscious awareness. </span><i><span
style="font-size:12pt;font-family:"Times New
Roman",serif">Physical Review E</span></i><span
style="font-size:12pt;font-family:"Times New
Roman",serif">, </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"
lang="EN-GB">94</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"
lang="EN-GB">, 052402 </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif"></span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><b><span
style="font-size:12pt;font-family:"Times New
Roman",serif;text-transform:uppercase"> </span></b></p>
<p class="MsoNormal"
style="text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif">D. M. Mateos, R. Wennberg, R. Guevara
Erra, J. L. Perez Velazquez</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span
lang="EN-GB">(2017) Consciousness as a global property of
brain dynamic
activity.</span></span><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> </span><i><span
style="font-size:12pt;font-family:"Times New
Roman",serif">Physical Review E,</span></i><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"
lang="EN-GB">96</span><span
style="font-size:12pt;font-family:"Times New
Roman",serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"
lang="EN-GB">,
062410 </span></p>
<p class="MsoNormal"
style="text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif"> </span></p>
<p class="MsoNormal"
style="text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="ES">J.L. Perez Velazquez, M.V.
Frantseva (2011). </span><i><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">The Brain-Behaviour
Continuum ―The
subtle transition between sanity and insanity</span></i><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">. Imperial College
Press/World Scientific </span></p>
<h1 style="margin:0cm 0cm
0.0001pt;text-align:justify;break-after:avoid;font-size:12pt;font-family:"Times
New Roman",serif"><span style="font-weight:normal"
lang="EN-US"> </span></h1>
<h1 style="margin:0cm 0cm
0.0001pt;text-align:justify;break-after:avoid;font-size:12pt;font-family:"Times
New Roman",serif"><span style="font-weight:normal">J. L.
Perez Velazquez</span><span style="font-weight:normal"> </span><span
style="font-weight:normal">(2009) </span><span
style="font-weight:normal" lang="EN-US">Finding
simplicity in complexity: general principles of biological
and nonbiological
organization.</span><span style="font-weight:normal"
lang="EN-US"> </span><i><span style="font-weight:normal">Journal
of Biological Physics</span></i><span
style="font-weight:normal">, 35, 209-221 </span></h1>
<p class="MsoNormal"
style="text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> </span></p>
<p class="MsoNormal"
style="text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB">R.
Stickgold (2001) Watching the sleeping brain watch us
—Sensory processing
during sleep. <i>Trends in Neurosciences</i>
24, 307. </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"> </span></p>
<p class="MsoNormal" style="margin:0cm 0cm
0.0001pt;text-align:justify;line-height:normal;font-size:11pt;font-family:Calibri,sans-serif"><span
style="font-size:12pt;font-family:"Times New
Roman",serif" lang="EN-GB"><br>
</span></p>
</div>
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</blockquote>
<p><br>
</p>
<pre class="moz-signature" cols="72">--
-------------------------------------------------
Pedro C. Marijuán
Grupo de Bioinformación / Bioinformation Group
<a class="moz-txt-link-abbreviated" href="mailto:pcmarijuan.iacs@aragon.es">pcmarijuan.iacs@aragon.es</a>
<a class="moz-txt-link-freetext" href="http://sites.google.com/site/pedrocmarijuan/">http://sites.google.com/site/pedrocmarijuan/</a>
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<a href="https://www.avast.com/antivirus">
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El software de antivirus Avast ha analizado este correo electrónico en busca de virus.
<br><a href="https://www.avast.com/antivirus">www.avast.com</a>
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