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PS2061: Brain and Behaviour lecture notes
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PS2061: BRAIN & BEHAVIOURCan Neuroscience explain the ghost in the machine?
The Human Brain:
➢ Consists of about 100 billion neurons..Each neutron can form between 5,000-200,000
connections with other neurons.
Levels of Organisation:
The Ghost in the Machine:
➢ Cartesian Dualism: Descartes recognised that mind and brain were inextricably linked,
but also separate.
➢ Many schools of thoughts in philosophical psychology.
Behaviourism:
➢ Behaviour can be researched scientifically without recourse to inner mental states.
➢ Free will is illusory, and all behaviour is determined by a combination of forces
(environment, genetics, etc).
➢ Mind may not exist and is not necessary to study it. Only input/output is important.
Materialism:
➢ Occams Razor: logical principle that the simple explanation is the best, and no extra
assumptions should be made.
➢ The only thing that can exist is ‘matter’. All things are composed of matter and
phenomenon are the result of material interactions, therefore the ‘mind’ must be a
property of matter (brain).
Monism to Dualism:
➢ Substance Dualism: Mind and matter are fundamentally different. (Science rejects).
➢ Property Dualism: even if mind comes from brain, subjective experience has properties
that cannot be reduced to brain states.
➢ Monism: identity theory. Mind = Matter in an absolute sense.
Property Dualism:
, ➢ ‘Non-reductive physicalism’: low level physical states (brain) cause higher level states
(eg. Mental state). But one cannot explain higher level effects in terms of lower-level
causes.
➢ Conscious experience cannot be explained by physical properties of the brain. Mental
properties are distinct from physical properties.
➢ Mind states come from brain states but we can’t explain mind states in terms of brain
states.
➢ They have ‘properties’ that are distinct from the properties of brains.
Functionalism:
➢ A form of Property Dualism.A response to behaviourism.
➢ The doctrine that what makes something in a mental state depends on the functions of the
brain such as sensory inputs and behavioural outputs.
➢ Assert that mental life can be explained in terms of higher-level functions.
➢ Assumes that info processing occurs at a level of abstraction that doesn’t depend on the
physical composition of a system.
Artificial intelligence: Connectionism
➢ An approach that explains mental phenomena using artificial neural networks.
➢ Memory is distributed in networks of neurons, such that experience is encoded
in the strength of connections between them.
➢ Parallel Distributed Processing (PDP):
– Inspired by the massively parallel nature of brain networks.
– Acquired knowledge is distributed across the network rather than at any single point
in the network.
➢ Backpropagation: is a way of training neural networks. The networks are
presented with training sets containing several examples of inputs along with
corresponding desired outputs.
– The extent of the difference between actual and desired outputs is the degree of
the error.
– Connections have values (‘weightings’) reflecting their strengths (the degree to
which an input can activate its target).
– The error signal is propagated backwards (in a sense, to ‘blame’ the layer above
the outputs). The initially random weightings are adjusted with learning until
errors are minimal.
Against Functionalism:
➢ Functionalism argues that in theory, even consciousness can be implemented
in any computer.
➢ John Searle (1980) argues: emulating the functional behaviour of the brain, or
some part of it, is insufficient grounds for attributing to a machine or computing
device the cognitive states such as those experienced by conscious beings like
ourselves.
➢ The Turing Test (1950s): A person converses ‘virtually’ with a another person
(A) and a computer (B) but does not know the true identity of either.
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