A simple mathematical model of the brain explains the pattern of murders by a serial killer, say researchers.
On 20 November 1990, Andrei Chikatilo was arrested in Rostov, a Russian state bordering the Ukraine. After nine days in custody, Chikatilo confessed to the murder of 36 girls, boys and women over a 12 year period. He later confessed to a further 20 murders, making him one of the most prolific serial killers in modern history.
Today, Mikhail Simkin and Vwani Roychowdhury at the University of California, Los Angeles, release a mathematical analysis of Chikatilo’s pattern of behaviour. They say the behaviour is well characterised by a power law and that this is exactly what would be expected if Chikatilo’s behaviour is caused by a certain pattern of neuronal firing in the brain.
Their thinking is based on the fundamental behaviour of neurons. When a neuron fires, it cannot fire again until it has recharged, a time known as the refractory period.
Each neuron is connected to thousands of others. Some of these will also be ready to fire and so can be triggered by the first neuron. These in turn will be connected to more neurons and so on. So it’s easy to see how a chain reaction of firings can sweep through the brain if conditions are ripe.
[…]The results are remarkably similar to the distribution of Chikatilo’s real murders and Simkin and Roychowdhury speculate that it would be relatively straightforward to introduce a realistic correction factor that would make the fit closer.
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Interestingly, Simkin and Roychowdhury’s work bares much similarity to other recent work suggesting that the distribution of epileptic fits also follows a power law. The reasoning here is the same too—that patterns of neuronal firing can spread through the brain, like an avalanche, causing a fit in the process.