Maths translates the language of the brain
Our intelligence, cognitive abilities and behaviour are the result of computations made by neurons inside the brain. To understand the function of the brain, it is necessary to measure the electrical activity of these neurons. Invasive procedures of investigation can only be carried out on animals. With humans, it is normally only possible to measure electrical potentials from the surface of the brain using an electroencephalogram (EEG).
Where do EEG data come from?
An EEG is a powerful tool that records the electrical activity of the brain by using electrodes placed over the scalp. It has been instrumental in the non-invasive study of brain function including perception, cognition and motor function in health and disease. EEG data come in the form of voltage spikes and waves, with the emerging fluctuations representing the electrical activity of many neurons. The anatomical localisation of the brain areas that produce a given topographical distribution of EEG voltage values is possible. Yet the underlying brain mechanisms that are responsible for these EEG oscillations remain unknown. Moreover, we cannot correlate EEG data with specific neural circuits in the brain, nor can we discriminate what types of neurons produce this activity. The core goal of the ESNECO project was to develop mathematical methods of analysis of brain surface EEGs that would allow scientists to estimate the activity and characteristics of different types of neurons inside the brain.
Mathematical approach to EEG data analysis
The research was undertaken with the support of the Marie Skłodowska-Curie Actions (MSCA) programme and focused on delivering a new set of mathematical algorithms to measure the activity of the neurons in the brain from EEG recordings. “The generated mathematical algorithm enabled us to analyse the EEG recording and translate the information into brain neural parameters and properties,” outlines project coordinator Stefano Panzeri. The ESNECO algorithm has immediate applications in both cognitive neuroscience research and clinical settings not only to understand the function of the human brain but also to track changes in brain activity during illness. Its use in cognitive neuroscience experiments will give scientists a better understanding of how the brain computes in normal conditions to achieve cognitive functions. What's more, applying it to clinical data will facilitate investigation into what actually happens in the brain during the various stages of certain disorders. This information is fundamental for deciding on and designing new interventions that could restore normal functions. According to Panzeri: “The next step for us is to distribute these algorithms so they can be applied to clinical data of autism spectrum disorders. This will help researchers to unveil the neural base of these disorders and design appropriate interventions.”
Keywords
ESNECO, brain, electroencephalogram, EEG, mathematical method, algorithm, neuron, voltage
