Optometry and Vision Sciences - Theses

Permanent URI for this collection

Search Results

Now showing 1 - 1 of 1
  • Item
    Thumbnail Image
    Functional organisation of the tammar wallaby visual cortex
    Jung, Young Jun ( 2020)
    How are the complex maps for feature selectivity created in the mammalian visual cortex? In most Eutherian mammals (e.g. cats, ferrets, tree shrews, and primates), orientation selective cells are organised into columns, which are arranged in pinwheel-like patterns across the cortex. However, rodents and rabbits do not have the same cortical structure: although they have robust orientation selectivity (OS) in individual cells, these are randomly distributed across the cortex in salt-and-pepper maps. Many studies have tried to explain how the complex maps for orientation preference (OP) are created in the primary visual cortex (V1). However, it remains unknown why some mammals have random salt-and-pepper OP maps while others have pinwheel OP maps. In the first chapter, we used intrinsic optical imaging to determine the cortical map structures in the V1 of a marsupial, the tammar wallaby (Macropus Eugenii). Marsupials represent a phylogenetically distinct branch of early mammals and we are the first to examine cortical map structures in a mammal that is not a member of the following mammalian Clades: Glires (e.g. rats, mice, squirrels), Laurasitheria (e.g. cats, ferrets) or Euarchonta (e.g. primates).We found clear orientation columns, arranged in pinwheel-like patterns across the cortex. Based on the finding of pinwheel maps in a marsupial and their similarity to those found in cats and primates, we proposed that the columnar organisation of OPs may be a primitive feature of the mammalian visual cortex and that the species in the Clade Glires (i.e. rodents and rabbits) are the unusual case in terms of mammalian visual brain organisation. We also proposed that the type of cortical map can be predicted by the central-to-peripheral ratio (CP ratio) of retinal ganglion cell (RGC) densities. Second, we extracellularly recorded and estimated the spatial RFs of neurons from the wallaby V1 and LGN in response to white-Gaussian noise (WGN) using 32-channel array probes. Single units were characterised using the nonlinear input model (NIM). We found that OS in the V1 of marsupial wallabies emerges from less selective LGN cell inputs, similar to cats and primates. Again, rodents and rabbits were found to be the odd ones out, suggesting that they have a unique neural circuitry different to other mammals. The NIM framework provided a far more comprehensive analysis of RF properties of neurons in the marsupial cortex, with greater variation in RF structures of simple and complex cells than reported based on simplistic F1/F0 analysis. In the final chapter, we extracted the extracellular spikes of V1 neurons and examined their spatial RFs using the NIM. Consistent with findings from cat V1, we found five distinct classes of extracellular spike waveforms in wallaby V1: regular spiking, fast spiking, triphasic spiking, compound spiking, and positive spiking. The five different spike waveforms were correlated to their spatial RF types and spiking characteristics. We found that negative spiking units showed characteristics typical of cortical cells, and the positive spiking units have similar RF types and spiking characteristics to the thalamic afferents that originate outside the cortex. Moreover, the RF properties of cortical neurons with positive spiking units resembled the wallaby LGN neurons we recorded in the study.