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Pauli, W. M.

Publications and source records attributed to Pauli, W. M..

2 recordsLinked to original sources

A data-driven approach to the automated study of cross-species homologies

Behavioral neuroscience has made great strides in developing animal models of human behavior and psychiatric disorders. Animal models allow for the formulation of hypotheses regarding the mechanisms underlying psychiatric disorders, and the opportunity to test these hypotheses using procedures that are too invasive for human participants. However, recent scientific reviews have highlighted the low success rate of translating results from animal models into clinical interventions in humans. A potential roadblock is that bidirectional functional mappings between the human and rodent brain are incomplete. To narrow this gap, we created a framework, Neurobabel, for performing large-scale automated synthesis of human neuroimaging data and behavioral neuroscience data. By leveraging the semantics of how researchers within each field describe their studies, this framework enables region to region mapping of brain regions across species, as well as cross-species mapping of psychological functions. As a proof of concept, we utilize the framework to create a functional cross-species mapping between the amygdala and hippocampus for fear-related and spatial memories, respectively. We then proceed to address two open questions in the field: (1) Do rodents have a dorsolateral prefrontal cortex? (2) Which human brain region corresponds to the rodent prelimbic cortex?

neuroscience

A High-Resolution Probabilistic In Vivo Atlas of Human Subcortical Brain Nuclei

Recent advances in magnetic resonance imaging (MRI) methods, including data acquisition, pre-processing and analysis, have enabled research on the contributions of subcortical brain nuclei to human cognition and behavior. At the same time, these developments have led to an increasing need for a high-resolution probabilistic in-vivo anatomical atlas of subcortical nuclei. In order to fill this gap, we constructed high spatial resolution, three-dimensional templates, using joint high accuracy diffeomorphic registration of T1- and T2- weighted structural images from 168 typical adults between 22 and 35 years old. In these templates, many tissue boundaries are clearly visible, which would otherwise be impossible to delineate in data from individual studies. The resulting delineation provides a more accurate parcellation of subcortical nuclei than current histology-based atlases. We further created a companion library of software tools for atlas development, to offer an open and evolving resource for the creation of a crowd-sourced in-vivo probabilistic anatomical atlas of the human brain.

neuroscience