Table Of ContentV. Srinivasa Chakravarthy
Demystifying
the Brain
A Computational Approach
Demystifying the Brain
V. Srinivasa Chakravarthy
Demystifying the Brain
A Computational Approach
123
V.Srinivasa Chakravarthy
Indian Institute of Technology Madras
Chennai, India
ISBN978-981-13-3319-4 ISBN978-981-13-3320-0 (eBook)
https://doi.org/10.1007/978-981-13-3320-0
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To,
Sri Aurobindo and the Mother
Preface
“The human brain is the most complex organ in the body” “The brain is the most
complexthingintheuniverse,”andtherefore,“Wewon’tbeabletounderstandthe
brain.” This is just a tiny bite of unqualified, unreasonable adulation that the brain
receivesinpopularliterature.Thereisaratherunhealthytendencyinpopularmedia
to portray the brain as some sort of a god-organ. It creates around the brain an
agnosticmystique,animpenetrableaurathatisonlymeanttobeadmiredbutnever
understood.
Thevagueandconfusingexplanationsofbrainfunctionthatareoftenofferedby
textbooks, and therefore by experts alike, do not help to dispel the mystique. For
example, planning and coordination are said to be the functions of the prefrontal
cortex, but cerebellum, the textbooks tell us, shares the same functions. Similarly,
memory is said to be the function of both the prefrontal cortex and hippocampus.
But why does the brain engage multiple systems to perform the same duty?
Consider another example of an explanation that does not explain much. The
thalamus,amassiveportaltosensoryinformationstreamingintothebrain,iscalled
a “relay system” which means that the thalamus merely passes on the influx of
signals beyond. But why does the brain need a whole complex organ to pass on
incomingsignalsintact;abundleoffiberswoulddothejob.Insuchsituations,asin
a thousand others, the eager student of neuroscience is quickly told answers to a
large number of questions of “what” category, but rarely “how” and almost never
“why.” Such a fundamental restriction makes the brain, despite all goodwill and
intent to understand on the part of an earnest student, unfathomable.
Thereasonbehindthismysteriousnessofthebrainisnotmerelyitscomplexity,
as popular media again would like us to believe. The A380 and the International
Space Station are no doubt some of the most complex systems that humans have
ever created. But we are able to handle and master that complexity because we
know the underlying physical principles. The complexity in the details can be
effectivelyhandledbyorganizingmanpowerorbytheuseofcomputationalpower.
Complexity can be mastered by comprehending the principles. When we separate
principlesfromthedetails,thecomplexitydoesnotdisappear butmerely ceasesto
vii
viii Preface
be intimidating. The sense of jaw-dropping wonder gives way to satisfaction that
comes from perfect understanding.
Butwhenitcomestobrainscience,thedistinctionbetweenprinciplesanddetails
varies from being weak to nonexistent. One wonders whether it is not just brain
science, but a good part of biology that suffers from this tendency. The strongly
descriptive and information-rich traditions of biology—particularly classical biol-
ogy—stand in stark contrast to modern physics and engineering where the princi-
ples are primary, and the details are handled effectively and effortlessly thereof.
This near lack of discrimination between principles and details in biology has
been brought to fore by molecular biologist Yuri Lazebnik in a regaling article
titled: “Canabiologistfixaradio?—Or,whatIlearnedwhile studying apoptosis.”
Lazebnikconsiders a quaint thoughtexperiment of how a biologistwould proceed
to understand the operation of a radio. Since biologists do not believe that physics
can be of much use in their pursuit, they launch their own, unique biology-style
attackontheproblemoftheradio.First,theywouldgetenoughfundsandprocurea
largenumberofradios.Theywouldthenembarkonaboldstudyoftheradiosand
their constituents in gruesome detail. The vast universe of radio components—
yellow and blue, spherical and cylindrical,striped and otherwise—ispainstakingly
mapped and embedded in an impressive taxonomy. That consummates a valorous
course of structural research on the subject.
Next follows a functional study. Our biologists with their unflagging energy
wouldnowbegintopluckoutcomponentsoftheradiooneatatimeandstudythe
effectofthemissingcomponentontheradio’skeyfunction—toproduceintelligible
sounds. This new line of effort may reveal that certain components are not crucial,
since when these are plucked out, the radio sputters and hisses but does not fail to
makeitselfheard.Butthereareothercomponents—perhapsawirethatconnectsthe
circuit board to the battery—in whose absence the radio is practically dead. The
discovery marks a tremendous breakthrough in our biologically inspired study
of theradio. It is doubtfulif this line of research would consummate in ahumanly
meaningful time frame.
By contrast, the study of radio that is armed with a prior understanding of
physical principles of the radio would proceed very differently. Basically, a radio
picksupelectromagneticsignalsfromtheambience,amplifiesthem,convertsthem
intoaudiblesounds,andplaysthem.Eachofthesestepsrequiresacertaindevice,a
mechanism, which can take a variety of possible physical implementations. But
onceweknowtheframework,theoverallpattern,wewouldlookforthesubstrates
for that pattern in the physical system and quickly identify them. While a
biology-styleinvestigationmaytakedecadestounravelaradio,anapproachbased
on an understanding of the underlying principles, assuming they are readily
available,mighttake a week ortwo, even incase of a radio of an extremely novel
design.
What then is the situation in neuroscience? Do we deal today in terms of
principlesofbrainfunction,orarewewillinglystuckinthequicksandofdetails?A
revolutionhasbeguninbrainscienceaboutthreedecadesago,thoughthefirstseeds
have been sown more than half a century ago. The goal of this revolution is to
Preface ix
answereverypossible“why”aboutthebrain,byunearthingtheprinciplesofbrain
function.Ithasgivenustherightmetaphor,apreciseandappropriatemathematical
language which can describe brain’s operations. By the application of these prin-
ciples, it is now possible to make sense of the huge sea of experimental data,
resolvelong-standingpointsofconfusion,andtrulybegintoadmirethearchitecture
of the brain. To borrow an analogy from astronomy, the new mathematics is
drawingusawayfromtheeraof“epicycles,”usheringintheeraof“inversesquare
law and Lagrangian dynamics.”
Researchers of the new computational and mathematical neuroscience have
unearthed a small set of principles of Neural Information Processing as they are
often called. As it happens in physics, researchers succeeded in explaining a wide
range of neural phenomena with the same compact set of principles. That set may
notbecomplete.Theremightbeotherprinciplesyettobediscovered.Butwhathas
already been discovered is enough to create confidence in the existence of such a
completeset.Thefirstoftheseprinciplesistheideathatinformationisstoredinthe
form of strengths of connections among neurons in the brain, and learning entails
appropriatemodificationoftheseconnections.Therearepreciserulesthatdescribe
such modification. Then, there is the idea that memories are stored as persistent
states,the“attractors,”ofbrain’sdynamicsortheideathatsynchronizedactivityof
neurons in distant parts of the brain has a great significance, not only to
sensory-motor function, but also to more intriguing phenomena like conscious
awareness. There are some more.
Thisbookisabouttheneuralinformationprocessingprinciples,sincetheaimof
this book is to demystify and deconstruct the brain. Chapter 1 in the book, as it
presents a brief history of ideas about the brain, also introduces some of the key
ideasandconcepts.Chapter2setsouttounderstandthelogicofbrain’sanatomy.It
takesthereaderonaquickjourneythroughtheevolutionarystagesinthebrainand
seeks to explain some of the broad stages in that development using the minimum
wire principle. Chapter 3 is an introduction to the neuron and mechanisms of a
neuron’s electrical and chemical signaling. Chapter 4 takes up the neuron model
just introduced and presents a simple mathematical model of the same. Using this
neuronal model, Chap. 4 shows how to construct complex networks that can
explain a variety of phenomena from psychology. Chapters 5 and 6, on memory
and brain maps, respectively, use mathematical models to explain how memories
arerepresentedinthebrainandhowtheformationofbrainmapscanbeexplained.
Chapters7and8describethearchitecturesofthebrainsystemsthatprocessvision
and touch senses, respectively. Chapter 9 is about motor function, about the brain
makeslifego.Chapter10presentsahistoryoftheoriesofemotionsandintroduces
some of the key neurobiological substrates of emotion processing. Chapter 11 on
language deals with the essential language circuits in the brain and describes how
words are represented and produced. It does not discuss more advanced aspects of
sentence-level processing. Chapter 12 takes up the conundrum of consciousness
x Preface
from a neuroscience perspective. After brieflytouchinguponseveralphilosophical
approachestotheproblem,itpresentssomeelegantexperimentalapproachestothis
intriguing question, concluding with an outline of some of the contemporary
neuroscientific theories of consciousness.
Chennai, India V. Srinivasa Chakravarthy
