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Detecting and Quantifying Topographic Order in the Brain

Research output: Contribution to conferencePoster

Original languageEnglish
Publication statusPublished - 2013
EventComputational and Systems Neuroscience (Cosyne) 2013 - Salt Lake City, Utah, United States
Duration: 28 Feb 20135 Mar 2013

Conference

ConferenceComputational and Systems Neuroscience (Cosyne) 2013
CountryUnited States
CitySalt Lake City, Utah
Period28/02/135/03/13

Abstract

Topographic maps are an often-encountered feature in the brains of many species. The degree and spatial scale of smooth topographic organisation in neural maps vary greatly, as do the sampling density and coverage of techniques used to measure maps. An objective method for quantifying topographic order would be valuable for evaluating differences between, e.g. experimental and control conditions, developmental stages, hemispheres, individuals or species; to date, no such method has been applied to experimentally-characterised maps. Neural maps are typically identified and described subjectively, but in cases where the scale of the map is close to the resolution limit of the measurement technique, just identifying the presence of a map can be a challenging subjective task. In such cases, an objective map detection test would be advantageous.

To address these issues, we assessed seven measures (Pearson distance correlation, Spearman distance correlation, Zrehen measure, topographic product, topological correlation, wiring length and path length) by quantifying topographic order in three classes of cortical map model: linear gradient, orientation-like, and randomly scattered homogeneous clusters. We found that the first five of these measures were sensitive to weakly-ordered maps and effective at detecting statistically significant topographic order, based on noisy simulated measurements of neuronal selectivity and sparse spatial sampling of the maps.

We demonstrated the practical applicability of these measures by using them to examine the arrangement of spatial cue selectivity in pallid bat primary auditory cortex5,6. This analysis shows for the first time that statistically significant systematic representations of inter-aural intensity difference and source azimuth exist at the scale of individual binaural clusters. An analysis based on these measures could be applied in any situation where it is useful to demonstrate the presence of a neural map, or to quantify the degree of order in a map.

Event

Computational and Systems Neuroscience (Cosyne) 2013

28/02/135/03/13

Salt Lake City, Utah, United States

Event: Conference

ID: 14802171