Over the last month and a half, I have been working through
a MOOC offered through Coursera. This is part of my professional development
for this year, to augment readings (summarised through this blog this year) in
the areas of neuroscience and neuropsychology.
The MOOC is offered through the Higher School of Economics
which is part of the National Research University located in Moscow. The presenter is Professor Vasily Klucharev.
The course has a traditional structure. Videos each week as lectures – usually
3 – 5 broken up into 5 -6 minutes to 20 minutes. Each video has one set of
multiple choice questions embedded. At the end of each week, a short multiple
choice test is completed. There is a time limit on the quiz and 3 attempts are
allowed. The exam at the end of the course is made up of 20 multiple choice
questions.
The above supplemented with a short collection of suggested
‘readings’ in the form of book chapters and journal articles. There is also an
active discussion forum which I have not had time to delve into but will try to
catch up on at some stage.
Part one introduces the topic. Neuroeconomics is an
interdisciplinary discipline to introduce aspects of psychology and
neuroscience into rationalist economics. The foundation and rationale of
neuroeconomics are introduced.
Week 2 goes through the neuroscience aspects required to
understand how neuroeconomics itself works. Various means of accessing brain
activity as decisions are made are also covered in week 2. Importantly, fMRIprocess is explained so that future graphs and explanations can be understood.
FMRI images are statistical combinations of structural (what is activated) and
functional (how often activated) brain activity. Brain activity is captured
through magnetic resonance of blood flow through the brain as laboratory tests
are completed by test subjects.
Week 3 begins the work on understanding how the brain goes
about making decisions. The concept of a diffusion model for decision making is
introduced and discussed in some depth.
Week 4 introduces the parts of the brain – the nucleusaccumbus (anticipates gain / reward), orbital frontal cortex (compares and
integrates information regarding reward outcomes) and the dorsolateralprefrontal cortex (does the control and planning). Examples are provided of how
each operates and then how all the brain sectors work in tandem to make value
judgements and decisions.
Week 5 brings in the important contributions of emotion into
how decisions are made. Emotions contribute either as innate or learnt
responses. The theory of emotion states we appraise, evaluate, take action,
make physiological changes or express through action. Emotional stimuli is thus
assigned a form of ‘value’ albeit, subjective values. Emotions are also the
product of brain activity and add a subjective dimension to how we make
decisions as how each person comes to a ‘conclusion’ is coloured by the
context, historical-social factors, ontology etc. etc. So, we hope to be
rational thinkers but perhaps we are nowhere near as rational as we would like
to be!
In week 6, the ways in which the brain makes decision either
as option 1 (intuitive, heuristic, automatic) or option 2 (reflective, analytic,
consciously monitored) are introduced. The role of the dorsallateral prefrontal
cortex (DLPFC) is brought in to explain how people modulate their needs through
self-control. Fairness and temporal discounting (delayed rewards) also plays a
role. Therefore, decisions not necessarily rational but impacted on by emotions
and the way various parts of the brain evaluate choices.
Week 7 brings in the contribution of ‘risk’, how does the
brain assess ‘risk’? Is there a difference between risk and uncertainty? The
ways in which we make decisions with an element of inherent risks is predicated
by how the options are framed. We tend to be risk adverse if we see a gain but
risk seeking when faced with a loss! Small probabilities are overweighted and
large probabilities under weighted. Therefore, we will gamble on an outcome
when faced with a losing proposition whereas if we perceive a sure win, we are
conservative.
The last two weeks of the course discusses ‘society and
brains’.
Week 8 discusses the ‘social brain’. Firstly, a video of
‘game theory’, the economics decision making model is presented. Revised the
levels of complexity in neuroeconomics – neuron – brain – cognitions and
emotions – society and biosphere. Social influences seen to be an evolutionary
factor (selection between genes, between individuals within a group and between
groups within a population). Correlation between social complexity and
neo-cortex volume in primates. Game theory used to try to understand situations
where decision-makers interact. Game consists of a set of actions and a payoff
function. Uses ‘prisoners’ dilemma’ to illustrate cooperation. The neurological
fundamentals of social cooperation are summarised with the role of mirror
neurons highlighted.
The last week of the course, brings in the dimensions of
evolution and the concept of humans as ‘economic animals’. The concept of
cooperation as being innate in humans and to a slightly less extend in primates
/ apes is used as example of neuro-based pre-disposal to certain traits.
Biological market theory is used to find out if there are natural examples of
the existence of market type scenarios in nature. For instance ‘cleaners’ /
groomers and ‘clients’ between animals – reef fish or anemones with small
schools of ‘cleaner’ fish. Clients allow cleaners to enter their mouths without
eating them. Monkeys have complex arrangements for grooming, with hierarchical
and supply based systems. Market systems impact on how services are
interchanged. Capuchin monkey experiments can be trained to trade coins for
tools to perform tasks – usually leading to a food reward. Capuchin monkeys
also learn value of coins, trading for ‘bargains’ and ‘gamble’ when loses are
framed as wins (i.e. loss aversion). Both capuchin monkeys and chimpanzees
reject unfair exchanges, indicating the perception of equality to be present in
primates.
Overall, a very traditionally structured course with content
delivered via weekly readings, video lectures, in lecture quizzes usually at
the end of the lecture, multiple choice quizzes at the end of each week that
count towards assessment and discussion forums. Took a couple of lectures to
get used to the professor’s accent but the explanations were clear and
powerpoint visuals usually helpful. The end of week quizzes were of variable
quality, with many written poorly but the standard of multi-choice question
construction did improve, so the lecturer was learning by doing and responding
to student suggestions.
I am now enrolled in a few more courses to the end of this
year to improve my understanding of neurobiology. These courses meet my
individualised learning needs and are useful for professional development but
you need to be committed to watching the hour or so of videos each week, taking
notes, thinking through the information before attempting the quizzes. I would
say I did learn lots of interesting facts and a couple of items I can apply to
current projects. Of note is the opportunity to be introduced to up to date thinking on brain function, albeit, from a specialised point of view.
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