ID 73 – Cortical parcellation based on local neuronal electrical activity. Issue 3 (March 2016) - Cottone, C.; Porcaro, C.; Cancelli, A.; Olejarczyk, E.; Salustri, C.; Tecchio, F.
Abstract : Brodmann's pioneering work resulted in the classification of the cortical areas based on their cyto-architecture and topology. Here, we aim at documenting that cortical areas can be also classified by neuronal activities specific to well identifiable structures and to the latter's networking within the whole brain. We investigated this notion in the primary somatosensory area (S1) and in the primary motor area (M1) in both hemispheres. Our results show that S1 and M1 are topologically differentiated by their respective neuronal activities, which are specific, independent of hemisphere and of subject's state (i.e., at rest, performing movements or receiving external stimulations). S1 displays higher power than M1 ( p  = .001) in the beta frequency band, while the opposite occurs in the gamma2 band ( p  = .034). We also show that the fractal dimensions (FD) emerged from our study as a strong index capable of differentiating the two brain areas in all subject's states, with S1's FD smaller than M1's ( p   <  .00001). The present work intends to be a first step toward the identification and classification of brain cortical areas via the dynamics of their neuronal activity, which we believe will advance our knowledge of the brain's intimate structural–functional unity.