NECO Lab | Universidad de Granada

  • Last updated on July the 28th of 2022

Computational NeuroScience


Computational neuroscience is the field of study in which computational tools and theories are used to investigate brain function. Specifically, in the laboratory, using recurrent neural networks of interacting excitatory and inhibitory neuronal populations, we aim to link parameters describing cortical circuit dynamics with properties of non-invasive neural recordings (EEG,MEG). We investigate and develop forward models to accurately describe how the recorded potentials are generated by neuronal activity. We use inverse models to infer parameters of the underlying cortical circuit from EEG and MEG data. A better description of the relationship between neural phenomena and non-invasive neural signals could improve existing tools for neuroscientific investigation of brain function, and could help with clinical diagnosis and development of drugs or other interventions to restore circuit-level properties that have been altered by brain disorders.

Head: Pablo Martínez Cañada.