Topological data analysis in functional neural networks under Ayahuasca effect.
Topological Data Analysis, Human Brain, Euler entropy, Persistent entropy, Ayahuasca, Neuroscience, Complex
Systems.
An area of great interest for scientists today is the study of real complex systems. An example of a complex system is
the human brain, an essential component of life. The present study makes use of complex systems methods to investigate, in an
exploratory way, the brain connectivity in a comparative way before and after the ingestion of Ayahuasca tea. The complex
systems tools used for this work focused on investigating the connectivity between brain regions, based on fMRI data. These
fMRI data were represented through simplicial complexes, in order to enable the use of specific techniques for the assessment
of brain connectivity. The three measures used to assess brain connectivity were: (i) Euler entropy; (ii) the curvature; (iii) and
persistent entropy. Using appropriate statistical tests, it was possible to observe changes in the phase transition point of the
complex system in question. For the curvature, no significant changes were observed, however a relevant change in the
participation profile of the nodes during the system phase transition was observed. As for the persistent entropy, a decrease in
its value was observed for the two-dimensional simplices. In this way, the present study expands the understanding of the
impact of Ayahuasca on the brain and opens the door to future studies regarding brain connectivity under the action of
psychedelics.