[Fis] new year lecture

[jose luis perez velazquez]

*Towards a statistical mechanics of cognition: **Consciousness as a global
property of brain dynamic activity *



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 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.

 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.

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.  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;
this is an important topic but we have no space to discuss it here (some of
these consideration are expounded in some chapters in ‘The Brain-Behaviour
Continuum―The subtle transition between sanity and insanity’ (Perez
Velazquez and Frantseva, 2011).

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. An entropy value was then computed for the number of possible
configurations of connected brain networks. The entropy of this macrostate
is given by the logarithm of the number of combinations. 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 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).

The following schematic figure summarises the main concept derived from the
study.


[image: image.png]



The figure 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.





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!). 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 (Stickgold, 2001). 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.

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.

The global nature of consciousness is advocated by several theories of
cognition. In fact, we think our 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.

In conclusion, and as 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.

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..





*References*

R. Guevara Erra, D. M. Mateos, R. Wennberg, J.L. Perez Velazquez
(2016) Statistical
mechanics of consciousness: Maximization of information content of network
is associated with conscious awareness. *Physical Review E*, 94, 052402



D. M. Mateos, R. Wennberg, R. Guevara Erra, J. L. Perez Velazquez (2017)
Consciousness as a global property of brain dynamic activity. *Physical
Review E,* 96, 062410



J.L. Perez Velazquez, M.V. Frantseva (2011). *The Brain-Behaviour Continuum
―The subtle transition between sanity and insanity*.  Imperial College
Press/World Scientific
  J. L. Perez Velazquez (2009) Finding simplicity in complexity: general
principles of biological and nonbiological organization. *Journal of
Biological Physics*, 35, 209-221



R. Stickgold (2001) Watching the sleeping brain watch us —Sensory
processing during sleep. *Trends in Neurosciences* 24, 307.
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