This is seriously
promising. Electrodes provide a direct
measurement, but data density is scant.
Focused magnetic fields inducing Faraday fields can be made vastly more
robust in terms of density and operated over an extended time frame.
Even better our theory does not
need to be particularly robust until a serious library of data is
accumulated. I very much like the fact
that the local circuitry is stimulated and we can then measure the effect and
its extensions.
Now take this program forward
to investigate luminous dreaming.
A New Method to
Measure Consciousness Proposed
It's an important new
tool for doctors, but what is it actually measuring?
http://www.scientificamerican.com/article.cfm?id=a-new-method-to-measure-consciousness-discovered
Leonardo
Da Vinci, in his Treatise on Painting
(Trattato della Pittura), advises painters to pay particular attention to
the motions of the mind, moti mentali.
“The movement which is depicted must be appropriate to the mental state of the
figure,” he advises; otherwise the figure will be considered twice dead:
“dead because it is a depiction, and dead yet again in not exhibiting motion
either of the mind or of the body.” Francesco Melzi, student and friend to Da
Vinci, compiled the Treatise posthumously from fragmented notes left to him.
The vivid portrayal of emotions in the paintings from Leonardo’s school shows
that his students learned to read the moti
mentali of their subjects in exquisite detail.
Associating an emotional expression of the
face with a “motion of the mind” was an astonishing insight by Da Vinci and a surprisingly modern metaphor. Today
we correlate specific patterns of electrochemical dynamics (i.e. “motions”) of
the central nervous system, with emotional feelings. Consciousness, the
substrate for any emotional feeling, is itself a “motion of the mind,” an
ephemeral state characterized by certain dynamical patterns of electrical activity.
Even if all the neurons, their constituent parts and neuronal circuitry
remained structurally the same, a change in the dynamics can mean the
difference between consciousness and unconsciousness.
But
what kind of motion is it? What are the patterns of electrical activity that
correspond to our subjective state of being conscious, and why? Can they
be measured and quantified? This is not only a theoretical or philosophical
question but also one that is of vital interest to the anesthesiologist trying
to regulate the level of consciousness during surgery, or for the neurologist
trying to differentiate between different states of consciousness following
brain trauma.
Recently,
Casali et al
have presented a quantitative metric. It provides, according to the authors, a
numerical measure of consciousness, separating vegetative states from minimally
conscious states. The study provides hints of being able to identify the
enigmatic locked-in state, in which the subject is conscious but is unable to
communicate with the external world due to motor deficits. What is most
interesting is the claim that the measures provide scientific insight into
consciousness, by providing an objective measure.
Their
metric, like other existing clinical measures of consciousness, is based on
Electroencephalography (EEG), where voltages recorded from electrodes placed on
the scalp provide a coarse picture of neural activity in the brain. EEG can be
used to measure either ongoing brain activity, or that evoked by an external
stimulus. In Casali’s case, the activity in question is evoked directly in
the brain using a transient magnetic field (Transcranial Magnetic
Stimulation). This involves applying a transient magnetic field, which
generates an electric field in a particular region of the brain due to
Faraday’s law, a bit like attaching a battery to the neural circuitry. This
causes currents to flow in the brain, not just in the stimulated region, but in
other regions connected to it as well. The spatial and temporal patterns of
these currents in the brain are then inferred from the EEG measurements and
quantified to produce the metric.
The
novelty in the study lies in the method used to quantify the spatiotemporal
distribution of current, which is also the basis of the theoretical claims. The
idea is that when the brain is unconscious, the evoked activity is either
localized (the authors call this “lack of integration”), or widespread and
uniform, as might be expected during slow wave sleep or epileptic seizures (“lack of
differentiation”). The conscious state on the other hand is supposed to
correspond to a distributed, but non-uniform spatiotemporal pattern of current
sources. The authors apply a standard data compression scheme (the Lempel-Ziv
algorithm, which is used for example in the GIF image format) to distinguish
between the two scenarios. The degree of compressibility of the current
distribution as inferred from EEG is the consciousness metric they propose.
The
scientists report that their measure performs impressively in distinguishing
states of consciousness within subjects, as well as across subjects in
different clinically identified consciousness stages. These promising results will no doubt
attract further study. However, the claim that the measure is theoretically
grounded in a conceptual understanding of consciousness deserves a closer look.
It is tempting to think that a concretely grounded clinical study of
consciousness naturally advances our scientific understanding of the
phenomenon, but is this necessarily the case?
It
is common in medicine to see engineering-style associative measurements,
measurements which aid pragmatic actions but do not originate from a
fundamental understanding. Physicians in antiquity were able to diagnose
diabetes mellitus (etymologically “sweet urine”, a reference to this original
diagnostic method), without any particular insights into the underlying
pathology. Clinical utility is not automatically a guarantee of scientific
understanding.
There
is reason to be cautious even in clinical terms. Some previous attempts to
numerically quantify consciousness have proven problematic,
a serious matter since awareness during surgery could lead to real suffering.
An anesthesiologist cautions in a commentary not to “trust the BIS or any other monitor
over common sense and experience.”
A human expert still remains the ultimate arbiter of the state of
consciousness of another human. This is unlikely to change soon.
There
are both practical and conceptual hurdles to developing a “consciousness
metric.” In practical terms, we have very little access to the details of
the neuronal dynamics in the human brain. DARPA, not shy of ambitious technical
challenges, has limited itself to 200 electrodes in a recent call for proposals to directly record from and stimulate the
human brain for deep brain stimulation therapy. That is about one billionth of
the estimated number of neurons in the brain. The EEG provides a very low
capacity, indirect measurement channel into the brain. If we can’t measure the
dynamics of the brain neurons in any detail, this could limit any attempt to
quantify consciousness.
However,
it is theoretically possible that even a limited measurement channel could
carry the necessary information. We are looking for a categorical judgment
between conscious and unconscious states, a single bit of information that can
be solicited from a conscious and communicative subject in an eye-blink or a
nod of the head. The conceptual hurdle is the more significant one. The
defining characteristic of the conscious state is that of subjective, first
person awareness, which fundamentally militates against objective measurements
by an independent observer, who can have no access to the primary phenomena
except through the subjective report of the conscious individual. It may be
possible (and useful) to obtain better and better correlative measurements of
this subjective report; but do the measurements themselves shed any light into
the phenomenon of consciousness?
To
clarify the underlying issues, consider a Turing-like test for consciousness
metrics. If a measure of consciousness is to have scientific status, it should
not ascribe a high degree of consciousness to a passive, inanimate system at
thermodynamic equilibrium. Otherwise we are left with some kind of pan-psychic
notion of consciousness. Nevertheless, a simple thought experiment shows that
it would be easy to construct such a system for the metric under discussion.
The
measure in question relies on the spatiotemporal patterns of currents invoked
by a transient magnetic field. However, Maxwell’s equations dictate that a
transient magnetic field will generate a pattern of currents in any chunk of
matter – matching up some distribution of those evoked currents is simply a
matter of the material properties. Consider for example a network of resistor,
capacitors and inductors with circuit time-constants tuned to be in the
hundred-millisecond range (to match EEG timescales). A radio antenna could be
used to detect the changing magnetic field and absorb its energy. It should not
be difficult to produce a circuit arrangement that produces a transient,
spatiotemporally non-uniform current distribution that is adequately
incompressible, and therefore fools the device into producing a high
consciousness score.
One
could also ask if the metric helps us answer a basic evolutionary question: can
it differentiate organisms into “conscious” and “non-conscious” categories?
While most neuroscientists would not hesitate to ascribe consciousness to
vertebrate animals or to invertebrates with complex brains
(think Octopus or Honeybee), they would hesitate when it comes to the
invertebrates with simpler nervous systems (Are Jellyfish conscious? How about
the Sponges?) Since the methodology under discussion has been prepared with
humans in mind, and ultimately depends on correlating with subjective
reporting, it is difficult to see how it could be extended across the
phylogenetic tree in a way that would help resolve these basic science
questions about consciousness.
Where
to look for measures of consciousness that advance our scientific
understanding? Most neuroscientists would agree that consciousness is
associated specifically with animal nervous systems (not trees or rocks).
Rather than look generically for abstract mathematical descriptions of
consciousness, we may need to specifically study the detailed architecture of
brain systems involved in arousal, attention, and so on. Complex animal nervous
systems have presumably evolved consciousness because it has some important
utility. If the architecture of brain systems involved in arousal shows
convergent evolution between invertebrates and vertebrates, this could give us
important scientific insights into consciousness as a biological phenomenon.
Better neurobiological insights into consciousness could in turn generate
advances in clinical measures.
We
have come a long way since Da Vinci, but human observers, in the form of teams
of expert physicians, remain essential to judging the subtleties of the
“motions of the mind” that we call consciousness. No matter how sophisticated
our tools, consciousness is still a core mystery with ample scope for
conceptual breakthroughs and creative thinking.
Are you a scientist who
specializes in neuroscience, cognitive science, or psychology? And have you
read a recent peer-reviewed paper that you would like to write about? Please
send suggestions to Mind Matters editor Gareth Cook, a Pulitzer
prize-winning journalist and regular contributor to NewYorker.com. Gareth is
also the series editor of Best American Infographics, and can be reached at
garethideas AT gmail.com or Twitter @garethideas.
ABOUT THE AUTHOR(S)
Partha
Mitra is Crick-Clay Professor at Cold Spring Harbor Laboratory. He obtained a
PhD in Theoretical Physics at Harvard and was a member of the Theory Group at
Bell Laboratories. He has written a book on analyzing brain
dynamics and is currently
engaged in mapping
mouse brain circuits.
You can follow him @partha_mitra
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