This is a question that scientists and philosophers have been grappling with for a very long time: can one form a thought without resorting to language? To find out, the famous neuroscientist Stanislas Dehaenne and Marie Amalric, a young researcher from his joint unit CEA/Inserm/Paris Sud and Collège de France, have developed an original experiment. They observed in vivo our brains forming a thought process that doesn't necessarily require the use of words. A mathematical reflection. And surprisingly, they have just revealed that the brain has a network of brain areas involved in both high-level mathematics and the simplest arithmetic operations. This network is activated by the mere sight of numbers. And it's totally independent of the networks of language.
Pwas there a thought without language? Brain imaging now makes it possible to ask this question in the laboratory. In order to determine which brain areas are involved in high-level mathematical thinking, neuroscientists (NeuroSpin, CEA/Inserm/University Paris Sud Saclay, Collège de France) have studied the brains of some fifteen professional mathematicians using functional MRI. The MRI images were acquired while they reflected for four seconds on high-level mathematical and non-mathematical assertions in order to judge them true, false or absurd. When they were reflecting on mathematical objects, a parietal and frontal backbone network of the brain was activated, which had no overlap with areas of language. Conversely, when they were asked to think about a problem in history or geography, the network that was activated was completely different from the mathematical regions and involved certain areas of language.
The network of brain areas uncovered in this study is not only involved in high-level mathematics, but also in the processing of number and mental arithmetic. Indeed, the researchers observed that this network was also activated in response to the simple sight of numbers or mathematical formulas among professional mathematicians as well as non-mathematicians (researchers at the same university level, but without scientific training) who had participated in this experiment.
Recent studies further suggest that this network is already involved in the identification of numbers in young children not yet attending school, and that it is very old in evolution as it is present when macaque monkeys recognize concrete objects. This implies that this network of brain areas pre-exists the learning of mathematics in school, and that it then develops with the education we receive. Indeed, the researchers found that the activation of the regions of this network was amplified in mathematicians compared to non-mathematicians. This observation coincides with the theory of neuronal recycling, developed by Stanislas DehaeneIt stipulates that high-level cultural activities, such as mathematics, recycle very ancient brain foundations in evolution, such as the sense of number, space or time.
There is thus a mathematical network in the brain, which is not that of language. This finding is consistent with other observations, such as the fact that some children or adults, who have a very poor numerical vocabulary, are able to perform advanced arithmetic operations, or that some aphasic patients can still do arithmetic and algebra.
In the age-old debate about thinking without language, mathematics has a special status. For some, such as Noam ChomskyA linguist, philosopher and professor at MIT, mathematical activity emerged in man as a consequence of his ability for language. Most mathematicians and physicists believe, on the contrary, that mathematical thinking is independent of language, such as Albert Einstein, who said: "Words and language, written or spoken, do not seem to play any role in my thinking mechanism. On the contrary, the basic building blocks of my thinking are signs or images, more or less clear, which I can reproduce and recombine at will".
References : Origins of the brain networks for advanced mathematics in expert mathematicians PNAS 2016; published ahead of print April 11, 2016, doi:10.1073/pnas.1603205113