Quantum Minds, Decisions, Language and more.
Amazon review of Paolo Legrenzi and Carlo Umiltas book.
January 8th, 2012 by Simon Laub.
Legrenzi and Umiltas book deals with
all of those colour photos of the brain,
that mass media inundates us with.
Pictures that apparently show us the precise location
in which a certain thought or emotion occurs in the brain.
Indeed, newspapers often carry articles that one area of the brain
governs falling in love, resisting temptation etc. illustrated by a
picture of a human brain with a coloured section. The news article then
explains that the coloured part becomes active when participants
in an experiment see their loved ones etc.
But do the newspaper readers really understand
the many steps that are needed to produce that picture of the
brain with the coloured area? And that each step is
based on assumptions, which are not always sound?
In the book, Legrenzi and Umilta takes us through some of the techniques involved,
from fMRI scanning to ''cognitive subtraction''.
And as the techniques are explained the assumptions also gets
- - -
Blood Flow and Activation.
According to Legrenzi and Umilta: The idea that ''the brains can be subdivided into a large number of portions (areas)
with different functions, which are independent of each
other, and that cerebral blood flow can be used to obtain information
about mental functions'' may seem a risky business.
According to the authors: Indeed, using blood flows to pinpoint
mental activity is both difficult and leads to problems.
One problem, that remains to be solved (according to Legrenzi and Umilta), is the question
of variations in blood flow, which have a latency of
5 seconds or more (i.e. it takes at least 5 seconds to get started).
Whereas, human thought on the other hand, has a latency of
just a few tens of milliseconds.
So, how (can we be sure that) is it possible
that very fast variations in thought are signalled by
much slower variations in cerebral blood?
The objective of neuroimaging is to identify the areas, which selectively
become active during any given task that requires the
intervention of known mental functions.
The cerebral areas are composed of a multitude of
nerve cells and neurons, whose need for oxygen
and glucose depends on the level of activation.
Therefore, knowing the quantity of blood feeding the various areas
at any given time, makes it possible to gauge the level of activation
of these areas.
In one method a radioactive isotope is injected into the blood stream.
Then the level of the isotope in various areas of the brain is measured
by using sensors placed around the patients head.
(In PET scans the radioactive isotope emits positrons which collide with
electrons, producing gamma rays, which are recorded by sensors around the
head of the patient).
In fMRI, the volunteers are placed in a magnetic field, which
aligns the hydrogen atoms present in water molecules circulating
in the blood (in the brain). When the hydrogen atoms
come into contact with radio-waves they resonate  - they emit
a quantity of radio-waves in proportion to their number -
The presence of large number of hydrogen atoms indicate
a high incidence of water, which again indicates
that the neurons are using large quantities of oxygen, indicating
a high activity.
Is another problem area for neuro-imaging, according to the authors.
First a control task must be identified. That is a task
which involves all the same mental functions of the experimental task
with the exception of the function whose neural bases you want to identify.
While each task is being executed, the activation of tiny
regions (voxels) of the brain is measured.
Then the level of activation in the control task is subtracted from
the activation in the experimental task.
If the result is greater than zero the neurons in the particular voxel is
more active in the experimental task than in the control task.
(It follows that an incorrect choice of control task leads
to an inaccurate conclusion).
However the level of activity in a voxel can also be due to chance factors.
So, normally a result would not be accepted unless it was
very unlikely to come about as a result of chance fluctuations.
- - -
Obviously, the brain still holds many secrets.
Brain science is not just: The discovery of a one to one connection between
a cognitive state and the activation of a brain area.
Thats not enough to say that a phenomenon has been
revealed and the problem has been solved...
Obviously not. Really understanding, how the brain works, takes many
more steps beyond establishing connections between
cognitive states and activations.
And, obviously, we shouldn't believe everything we read in the newspapers.
The book certainly explains to us that we should be careful
when neuro images are presented to us.
A good place to start, as we venture further into the frontiers of brain-land.
Evolution of Language.
New Scientist cover story, December 10th 2011.
December 10th, 2011 by David Robson.
''If you take a chimp born in London Zoo and place it back in its African homeland,
it will have little trouble communicating. Thats because all chimps share
a small repertoire of grunts, barks and hoots.''
Humans need to be more flexible. Our brains can handle a huge range of abstract
concepts. So we have evolved an open-ended form of communication
to express our thoughts.
Starting from phonemes, discrete sounds, we can put these discrete sounds together
in elaborate combinations to make words and sentences (structured by grammar).
Currently, there are more than 7.000 human languages.
Around 60 per cent of the worlds 7.000 languages are found in the tropics.
The richest place is Papua New Guinea, home to 1 in 7 of the worlds languages.
Over the millenia, is is estimated that cultural evolution has carved out
thousands of mutually unintelligible tongues. Mark Pagel at the University of Reading
estimates that half a million languages may have lived and died since modern humans
Language Diversity and Migrations: According to the ''serial founder effect'' human genetic diversity declines
as you get further away from Africa: ''Bands of migrating humans took only a subset
of genes from the gene pool in their place of origin, reducing genetic diversity
as they migrated further and further away (from Africa).''
Migration might have whittled down language in a similar way. As groups splintered
off the ancestral population in Africa, they might have left behind some of the
the lesser used phonemes (only spoken in minority dialects).
An analysis of 504 languages offers some support for the theory. Whith the highest phoneme
diversity in Africa and the lowest in South America and Oceania.
Genetic Influences: Another influence on language diversity may be hidden in our genes.
Certain variants of two genes (associated with brain development) are more common in
places where people speak tonal languages (if these genes help people
differentiate between pitches, then in areas were they are common they will
push language towards a tonal system).
Language Grammars: Languages have vastly divergent grammars. The diversity is mystifying until
you look at who speaks the language. In an analysis of 2.000 languages
it has been demonstrated that complex grammars are more common in small languages
(whose speakers have little contact with outsiders). Those with simpler
rules - English, Mandarin - tend to be spoken by larger populations
that have contact with lots of other societies.
Latin had complex rules: As adults in the provinces began to learn the
lingo, they simplified it into vulgar forms that eventually became Italian,
Spanish, French - which lacks Latins complexities.
''The hunt is now on for more laws that dictate the evolution of languages'',
according to Quentin Atkinson .
For more about human evolution, see my review of Martin Merediths Born in Africa.
Sharon Begley and Jean Chatzkys Time report on NeuroEconomics,
November 14th 2011.
Studies suggest that our brains might be hard-wired when it comes to spending....
Indeed: ''Pleasure now, is worth more to us than pleasure later.
We much prefer current consumption to future consumption.
It may even be wired into us'', according to economist William Dickens of Northeastern University.
In one experiment, neuroeconomist Paul Glimcher of New York University wanted
to see what it would take for people to willingly delay gratification.
He gave a dozen volunteers a choice: $20 now, or more money later on (from $20.25 to $110).
One volunteer would agreed to wait 1 month to take $21 dollars. But, at the other end of the
spectrum, another volunteer would only agree to wait a month if he received $68
( I.e. when he wants something he wants it now). And he was not alone. The number of people
in the category
''spend-it-now, to-hell-with-tomorrow'' (who seek immidiate gratification) has increased in recent years.
In the other people - the high delayers - the brain's thoughtful, rational
prefrontal cortex was more active, as was the right inferior frontal gyrus,
which inhibits the ''I want it now'' impulse.
Poor delayers had less activity in both regions, but higher activity in
regions of the limbic system that respond to instant gratification.
Obviously, identifying the regions of the brain that control such impulses is a
first step in learning how to strengthen them and, ultimately, to enjoy saving.
Indeed, at least one center for such activity has been discovered:
The dorsolateral PFC, in particular, sends ''calm down'' signals to the
midbrain's ''I want it now'' circuits. As a result: ''In studies that
use strong magnets to temporarily disable the dorsolateral PFC
on human volunteers, people get more impulsive.''
Since zapping your brain, to activate or deactivate the dorsolateral PFC,
is not so simple as it sounds - scientist have searched for other
techniques to help the brain save money.
According to neuro-economist Paul Zak of Claremont Graduate University:
The size of the dorsolateral PFC differs hugely from one person to another.
As does its number and strengths of connections to the midbrain.
However, with the plasticity of the adult brain it should eventually be possible to increase
the number or strength of these connections (through training etc.), so that the midbrain would
receive more calming signals....
''If you defer gratification, the payoff can be be greater than with immidiate
gratification, but your brain has to learn that'', according to Paul Zak.
Paul Zak also find that a squirt of the hormone oxytocin, the love hormone - because
of the role it plays in pair bonding - makes people more patient:
If you grow up in an environment with short time horizons,
of course you are going to satisfy your desires as quickly as you can.
According to Viginia Techs Bickel :
''Unless you are trained to control your impulses, why would you?
Instant gratification is fun, and that is what society teaches us.
What life teaches us, however, is another matter''.
New Scientist cover story, November 12th 2011.
November 12th, 2011 by Kate Douglas.
In Decision Theory . humans are supposed to be ''rational optimizers'': ''Given a choice, we should weigh up each option, considering its value and
probability, and then choose the one with the highest expected utility.''
Well, so it would be, if humans were logical computers or all knowing beings.
Alas, we are not. Instead, humans are biological beings shaped by evolution.
And our decisions are shaped by innate biases, emotions, expectations,
misconceptions, conformity etc...
Each day we face between 2.500 - 10.000 decisions. Ranging from minor concerns,
such as which brand of coffee to drink, to big questions, like who we should marry.
There simply isn't enough time to process all of this consciously.
So, many of these decisions are made by the subconscious
A mind with many quirky mental biases:
Anchoring effect: In Novel situations, where information is limited,
we have an unfortunate habit of basing decisions on random connections .
(One study found that asking people to write down high numbers,
would subsequently affect future decision-making and information analysis).
Confimation bias: Our tendency to overemphasise anything that confirms
what we already believe.
Short-term bias: We tend to prefer smaller rewards now to bigger ones later.
Decision fatigue: Making decisions is hard work. So, when we are tired, we tend not
take decisions that change the status quo (E.g. Judges are four times more likely to
grant bail in the morning than in the afternoon...).
For more examples, see my review of Jonah Lehrers book The Decisive Moment.
No, we are not logical computers, we don't practise the
''economic rationality'' of traditional decision theory - Instead we
practise ''biological rationality''.
According to Alex Kacelnik of Oxford University:
We are swayed by our changing internal states - hunger, thirst, libido -
tailoring our choices to our needs.
Sometimes we even eschew choice altogether and simply follow the herd.
According to Rob Boyd from the University of California, Los Angeles:
''We have evolved to learn from others, because this is often a wise
option. In most situations it is way beyond an individuals capacity to
know the best thing to do. But we are good at recognising who to copy.''
Still, knowing how we actually make decisions is obviously essential,
if we want to improve even just a little bit. And with so much still to learn, it follows that perfect decision-making
is probably not going to come about any time soon.
According to Kate Douglas: Decision making is indeed difficult. But, ''
Of all the choices the you face everyday, the decision to try to make
better decisions is surely the biggest no-brainer.''
New Scientist cover story, September 3rd. 2011.
September 3rd, 2011 by Mark Buchanan.
A very interesting cover story in this weeks NewScientist.
According to Mark Buchanan: The fuzziness and weird logic of the way particles behave, -
applies surprisingly well to how humans think..
In psychologists Amos Tversky and Eldar Shafirs, of Princeton University,
gambling experiment - players are told they have an even chance of winning
$200 or losing $100. And were then asked to play the game a second time.
When told they had won the first gamble, 69 percent chose to play again.
If told they had lost, only 59 percent wanted to play again.
No big surprises with this. But when people were not told the outcome
of the first outcome - only 36 percent wanted to play again!
This violates classical logic and something that logicians
call ''the sure thing principle''. If you prefer tea over coffee
before noon, and tea over coffee after noon. Then you should prefer tea over coffee,
if you don't know the time. Apparently, not so with people!
Quantum probabilities on the other hand might have the potential
to provide a framework for modelling human decision making.
In the quantum world, events A and B are described by quantum
amplitudes - to work out what is happening amplitudes are squared and
an ''interference term'' is added.
And apparently such quantum logic fit human behaviour much better in some situations!
According to Peter Bruza at Queensland University in Brisbane, Australia:
''The reason has to do with our finite brain being overwhelmed
by the complexity of the environment, yet having to take action
long before it can calculate its way to the certainty demanded by
classical logic. Quantum logic may provide solutions
that work well enough, even if they are not
In Buchanans words:
This doesn't mean that the human brain have anything to do with
quantum physics, only that the mathematical
language of quantum theory happens to match the description of human decision-making.