Identification of Functionally Interconnected Neurons Using Factor Analysis

SOLETTA, JORGE H.; FARFÁN, FERNANDO D.; ALBARRACÍN, ANA L.; PIZÁ, ALVARO G.; LUCIANNA, FACUNDO A.; FELICE, CARMELO J.

Computational Intelligence and Neuroscience

Hindawi

Año: 2017 vol. 2017 p. 1 - 11

1687-5265

The advances in electrophysiological methods have allowed registering the joint activity of single neurons. Thus, studies onfunctional dynamics of complex-valued neural networks and its information processing mechanism have been conducted.Particularly, the methods for identifying neuronal interconnections are in increasing demand in the area of neurosciences.Here, weproposed a factor analysis to identify functional interconnections among neurons via spike trains. Thismethod was evaluated usingsimulations of neural discharges from different interconnections schemes.The results have revealed that the proposed method notonly allows detecting neural interconnections but will also allow detecting the presence of presynaptic neurons without the needof the recording of them.