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A CONTROVERSIAL computer test for schizophrenia has been astonishingly
accurate in early trials. Its inventors say the test, which is based on a
learning system called a neural network, could even diagnose the condition
before subjects show any symptoms.

Early trials have shown the program to be 100 per cent accurate. If further
trials are as successful, it could allow early treatment of the disease, before
it has had time to progress.

The system was developed at the University of British Columbia in Vancouver
by Peter Liddle, a psychiatrist specialising in brain imaging. It uses a neural
network to analyse the brain scans of patients, looking for telltale
characteristics in cerebral blood flow. 鈥淥ne of the big challenges with
schizophrenia is the diagnosis. It can take several years for it to be made
clear,鈥� says Liddle. 鈥淏eing able to make a reliable diagnosis early can help to
optimise the outcome.鈥�

But some researchers are sceptical that brain imaging can provide all the
answers. 鈥淣obody has ever found a specific brain abnormality that all
schizophrenics have that nobody else has,鈥� warns Robin Murray of the Institute
of Psychiatry in London.

Liddle鈥檚 system relies upon recent evidence suggesting that certain parts of
the brain are disrupted in people with schizophrenia. In addition, activity at
these sites differs between patients and healthy controls while they are
carrying out verbal memory tasks.

According to Liddle, these anomalies might reflect the underlying causes of
schizophrenia, making it possible to detect the condition much earlier. But the
differences tend to be subtle, he explains. 鈥淭his method seems to have the
ability to pull out relatively complex patterns that the naked eye wouldn鈥檛 be
able to see,鈥� he says.

Ironically, the neural network is a computer program modelled on the human
brain. It learns from experience, just as people do. Clusters of software
processors, called nodes, are designed to behave like brain cells, weighting
different attributes from an array of inputs according to their importance. The
network has to be trained on known sample inputs, and the weightings are
adjusted to produce the desired result. The program then responds to novel
inputs in the same way.

Liddle鈥檚 neural network examines blood flow in the temporal and parietal
lobes, looking for what its training has told it are the idiosyncrasies of
schizophrenia. His network was trained on positron emission tomography scans
taken from seven schizophrenia patients and two healthy subjects.

After looking at scans from four healthy subjects and nine patients diagnosed
as having schizophrenia, it was able to differentiate between them with 100 per
cent accuracy. 鈥淭his has a really significant potential,鈥� says Pat Levitt, a
neuroscientist at the University of Pittsburgh in Pennsylvania. He says there
are different types of schizophrenia鈥攚hich are treated in different
ways鈥攂ut it鈥檚 difficult to categorise patients. If doctors could use the
program to classify patients, they would be able to treat them with a greater
degree of certainty, he adds.