|Friday, April 24
Franco Pestill, PhD
(Psychology, Neuroscience and Cognitive Science, Indiana University)
Software project: francopestilli.github.io/life
Innovation for in-vivo white-matter mapping using LiFE and ensemble tractography
Magnetic resonance diffusion imaging and computational tractography are the only technologies that enable neuroscientists to measure white matter in the living human brain. In the decade since their development, these technologies revolutionized our understanding of the importance of the human white-matter for health and disease. The white matter pathways comprise a set of active wires and the responses and properties of these wires predict human cognitive and emotional abilities in health and disease. Beside excitement, the need for a systematic approach to tractography validation (Pestilli Scientific Data 2015) and a framework to perform statistical model testing can be seen in recent reports in Science that set out to characterize human white matter structure (Van Wedeen et al., Science 2011; Catani et al., Science 2011).
I will present a new method (LiFE, Linear Fascicle Evaluation) to perform both tractography validation and statistical hypotheses testing on the network of brain connections (Pestilli et al., Nature Methods 2014). These new methods improve current techniques in fundamental ways and can be applied to any type of diffusion data. I will show that by using the methods we were able to identify a major white-matter pathway communicating information between the dorsal and ventral visual streams, the Vertical Occipital Fasciculus (VOF; Yeatman, Wiener, Pestilli et al., PNAS 2014; Takemura et al., Cerebral Cortex, In Press).
Beyond the advances to in-vivo white-matter mapping, it is agreed that there is need to improve tractography methods (Sporns, Nature Methods 2012; Catani et al., 2011). I will present a new approach to tractography. Ensemble tractography (Takemura, Wandell and Pestilli, under review) uses the LiFE method and combines a series of connectomes generated with a variety of tractography algorithms and parameters set. We show that Ensemble tractography improves the representation of the white-matter in living brains by best exploiting available data. Connectomes generated using ensemble tractography are denser and represent a wide variety of white-matter properties. For example, connectomes contain both long-range white matter tracts as well as short range u-fibers. These methods can being used to improve the precision by white-matter tracts and connections that can be mapped and to related their properties to human perception and cognition.