Knowledge Synthesis with Maps of Neural Connectivity

Abstract

This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called “Knowledge Engineering from Experimental Design” (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features.

Combining collation and annotation efforts toward completion of the rat and mouse connectomes in BAMS

“…This approach is necessary for qualitatively capturing the topographical details of terminal fields, and the axonal pathways and their routes. It is also useful for any neuroinformatic system that aims to reconstruct macroconnections in visual format (Tallis et al, 2011 ).…”

Mapping Molecular Datasets Back to the Brain Regions They are Extracted from: Remembering the Native Countries of Hypothalamic Expatriates and Refugees

“…One methodology for representing this context in a general way is based on the relationships between independent and dependent variables within studies. This may serve as a convenient framework for describing neuroanatomically grounded data by treating the location of the phenomena of interest in the brain simply as one of several independent variables that describe the context of a particular datum [377, 428]. …”

Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience

“…The Ontology for Biomedical Investigations (Bandrowski et al, 2016 ) and the Evidence Ontology (Chibucos et al, 2014 ) are two recent knowledge bases that include epistemic elements (below, we outline quantitative approaches to such concepts). Knowledge-Engineering from Experimental Design (KEfED) is a formalism that captures both ontological and epistemological information by representing not only experimental findings but also semantic elements of the experiments themselves (Russ et al, 2011 ; Tallis et al, 2011 ). KEfED is based on the “Cycle of Scientific Investigation” (CoSI), a model in which (i) experiments induce observational and then interpretational assertions, and (ii) domain knowledge motivates hypotheses and then experimental designs (Russ et al, 2011 ).…”