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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>
    <blockquote type="cite"
cite="mid:CAH2XT=-HschvH_WxCemFN6e33n0LES996pWjgSuKw_++nCMdrw@mail.gmail.com">
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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>
      <br>
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      <br>
      <pre wrap="">_______________________________________________
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</pre>
    </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>
------------------------------------------------- </pre>
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